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  2021 (7)
Selective Classification via One-Sided Prediction. Gangrade, A.; Kag, A.; and Saligrama, V. In Banerjee, A.; and Fukumizu, K., editor(s), The 24th International Conference on Artificial Intelligence and Statistics, AISTATS 2021, April 13-15, 2021, Virtual Event, volume 130, of Proceedings of Machine Learning Research, pages 2179–2187, 2021. PMLR
Selective Classification via One-Sided Prediction [link]Paper   bibtex  
Federated Learning Based on Dynamic Regularization. Acar, D. A. E.; Zhao, Y.; Navarro, R. M.; Mattina, M.; Whatmough, P. N.; and Saligrama, V. In 9th International Conference on Learning Representations, ICLR 2021, Virtual Event, Austria, May 3-7, 2021, 2021. OpenReview.net
Federated Learning Based on Dynamic Regularization [link]Paper   bibtex  
Debiasing Model Updates for Improving Personalized Federated Training. Acar, D. A. E.; Zhao, Y.; Zhu, R.; Navarro, R. M.; Mattina, M.; Whatmough, P. N.; and Saligrama, V. In Meila, M.; and Zhang, T., editor(s), Proceedings of the 38th International Conference on Machine Learning, ICML 2021, 18-24 July 2021, Virtual Event, volume 139, of Proceedings of Machine Learning Research, pages 21–31, 2021. PMLR
Debiasing Model Updates for Improving Personalized Federated Training [link]Paper   bibtex  
Memory Efficient Online Meta Learning. Acar, D. A. E.; Zhu, R.; and Saligrama, V. In Meila, M.; and Zhang, T., editor(s), Proceedings of the 38th International Conference on Machine Learning, ICML 2021, 18-24 July 2021, Virtual Event, volume 139, of Proceedings of Machine Learning Research, pages 32–42, 2021. PMLR
Memory Efficient Online Meta Learning [link]Paper   bibtex  
Training Recurrent Neural Networks via Forward Propagation Through Time. Kag, A.; and Saligrama, V. In Meila, M.; and Zhang, T., editor(s), Proceedings of the 38th International Conference on Machine Learning, ICML 2021, 18-24 July 2021, Virtual Event, volume 139, of Proceedings of Machine Learning Research, pages 5189–5200, 2021. PMLR
Training Recurrent Neural Networks via Forward Propagation Through Time [link]Paper   bibtex  
Surprisingly Simple Semi-Supervised Domain Adaptation with Pretraining and Consistency. Mishra, S.; Saenko, K.; and Saligrama, V. CoRR, abs/2101.12727. 2021.
Surprisingly Simple Semi-Supervised Domain Adaptation with Pretraining and Consistency [link]Paper   bibtex  
Effectively Leveraging Attributes for Visual Similarity. Mishra, S.; Zhang, Z.; Shen, Y.; Kumar, R.; Saligrama, V.; and Plummer, B. A. CoRR, abs/2105.01695. 2021.
Effectively Leveraging Attributes for Visual Similarity [link]Paper   bibtex  
  2020 (19)
Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers. Ma, Y.; Olshevsky, A.; Szepesvári, C.; and Saligrama, V. J. Mach. Learn. Res., 21: 133:1–133:36. 2020.
Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers [link]Paper   bibtex  
Zero Shot Detection. Zhu, P.; Wang, H.; and Saligrama, V. IEEE Trans. Circuits Syst. Video Technol., 30(4): 998–1010. 2020.
Zero Shot Detection [link]Paper   doi   bibtex  
Minimax Rank-\textdollar1\textdollar Matrix Factorization. Saligrama, V.; Olshevsky, A.; and Hendrickx, J. M. In Chiappa, S.; and Calandra, R., editor(s), The 23rd International Conference on Artificial Intelligence and Statistics, AISTATS 2020, 26-28 August 2020, Online [Palermo, Sicily, Italy], volume 108, of Proceedings of Machine Learning Research, pages 3426–3436, 2020. PMLR
Minimax Rank-\textdollar1\textdollar Matrix Factorization [link]Paper   bibtex  
Budget Learning via Bracketing. Acar, D. A. E.; Gangrade, A.; and Saligrama, V. In Chiappa, S.; and Calandra, R., editor(s), The 23rd International Conference on Artificial Intelligence and Statistics, AISTATS 2020, 26-28 August 2020, Online [Palermo, Sicily, Italy], volume 108, of Proceedings of Machine Learning Research, pages 4109–4119, 2020. PMLR
Budget Learning via Bracketing [link]Paper   bibtex  
Don't Even Look Once: Synthesizing Features for Zero-Shot Detection. Zhu, P.; Wang, H.; and Saligrama, V. In 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2020, Seattle, WA, USA, June 13-19, 2020, pages 11690–11699, 2020. IEEE
Don't Even Look Once: Synthesizing Features for Zero-Shot Detection [link]Paper   doi   bibtex  
RNNs Incrementally Evolving on an Equilibrium Manifold: A Panacea for Vanishing and Exploding Gradients?. Kag, A.; Zhang, Z.; and Saligrama, V. In 8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020, 2020. OpenReview.net
RNNs Incrementally Evolving on an Equilibrium Manifold: A Panacea for Vanishing and Exploding Gradients? [link]Paper   bibtex  
Minimax Rate for Learning From Pairwise Comparisons in the BTL Model. Hendrickx, J. M.; Olshevsky, A.; and Saligrama, V. In Proceedings of the 37th International Conference on Machine Learning, ICML 2020, 13-18 July 2020, Virtual Event, volume 119, of Proceedings of Machine Learning Research, pages 4193–4202, 2020. PMLR
Minimax Rate for Learning From Pairwise Comparisons in the BTL Model [link]Paper   bibtex  
Piecewise Linear Regression via a Difference of Convex Functions. Siahkamari, A.; Gangrade, A.; Kulis, B.; and Saligrama, V. In Proceedings of the 37th International Conference on Machine Learning, ICML 2020, 13-18 July 2020, Virtual Event, volume 119, of Proceedings of Machine Learning Research, pages 8895–8904, 2020. PMLR
Piecewise Linear Regression via a Difference of Convex Functions [link]Paper   bibtex  
Low Dimensional Visual Attributes: An Interpretable Image Encoding. Zhu, P.; Zhu, R.; Mishra, S.; and Saligrama, V. In Bimbo, A. D.; Cucchiara, R.; Sclaroff, S.; Farinella, G. M.; Mei, T.; Bertini, M.; Escalante, H. J.; and Vezzani, R., editor(s), Pattern Recognition. ICPR International Workshops and Challenges - Virtual Event, January 10-15, 2021, Proceedings, Part III, volume 12663, of Lecture Notes in Computer Science, pages 90–102, 2020. Springer
Low Dimensional Visual Attributes: An Interpretable Image Encoding [link]Paper   doi   bibtex  
RNN Training along Locally Optimal Trajectories via Frank-Wolfe Algorithm. Yue, Y.; Li, M.; Saligrama, V.; and Zhang, Z. In 25th International Conference on Pattern Recognition, ICPR 2020, Virtual Event / Milan, Italy, January 10-15, 2021, pages 10532–10539, 2020. IEEE
RNN Training along Locally Optimal Trajectories via Frank-Wolfe Algorithm [link]Paper   doi   bibtex  
Limits on Testing Structural Changes in Ising Models. Gangrade, A.; Nazer, B.; and Saligrama, V. In Larochelle, H.; Ranzato, M.; Hadsell, R.; Balcan, M.; and Lin, H., editor(s), Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual, 2020.
Limits on Testing Structural Changes in Ising Models [link]Paper   bibtex  
Learning to Approximate a Bregman Divergence. Siahkamari, A.; Xia, X.; Saligrama, V.; Castañón, D. A.; and Kulis, B. In Larochelle, H.; Ranzato, M.; Hadsell, R.; Balcan, M.; and Lin, H., editor(s), Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual, 2020.
Learning to Approximate a Bregman Divergence [link]Paper   bibtex  
Online Algorithm for Unsupervised Sequential Selection with Contextual Information. Verma, A.; Hanawal, M. K.; Szepesvári, C.; and Saligrama, V. In Larochelle, H.; Ranzato, M.; Hadsell, R.; Balcan, M.; and Lin, H., editor(s), Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual, 2020.
Online Algorithm for Unsupervised Sequential Selection with Contextual Information [link]Paper   bibtex  
Budget Learning via Bracketing. Gangrade, A.; Acar, D. A. E.; and Saligrama, V. CoRR, abs/2004.06298. 2020.
Budget Learning via Bracketing [link]Paper   bibtex  
Piecewise Linear Regression via a Difference of Convex Functions. Siahkamari, A.; Gangrade, A.; Kulis, B.; and Saligrama, V. CoRR, abs/2007.02422. 2020.
Piecewise Linear Regression via a Difference of Convex Functions [link]Paper   bibtex  
RNN Training along Locally Optimal Trajectories via Frank-Wolfe Algorithm. Yue, Y.; Li, M.; Saligrama, V.; and Zhang, Z. CoRR, abs/2010.05397. 2020.
RNN Training along Locally Optimal Trajectories via Frank-Wolfe Algorithm [link]Paper   bibtex  
Selective Classification via One-Sided Prediction. Gangrade, A.; Kag, A.; and Saligrama, V. CoRR, abs/2010.07853. 2020.
Selective Classification via One-Sided Prediction [link]Paper   bibtex  
Online Algorithm for Unsupervised Sequential Selection with Contextual Information. Verma, A.; Hanawal, M. K.; Szepesvári, C.; and Saligrama, V. CoRR, abs/2010.12353. 2020.
Online Algorithm for Unsupervised Sequential Selection with Contextual Information [link]Paper   bibtex  
Limits on Testing Structural Changes in Ising Models. Gangrade, A.; Nazer, B.; and Saligrama, V. CoRR, abs/2011.03678. 2020.
Limits on Testing Structural Changes in Ising Models [link]Paper   bibtex  
  2019 (18)
Probabilistic Semantic Retrieval for Surveillance Videos With Activity Graphs. Chen, Y.; Wang, J.; Bai, Y.; Castañón, G. D.; and Saligrama, V. IEEE Trans. Multim., 21(3): 704–716. 2019.
Probabilistic Semantic Retrieval for Surveillance Videos With Activity Graphs [link]Paper   doi   bibtex  
Cost aware Inference for IoT Devices. Zhu, P.; Acar, D. A. E.; Feng, N.; Jain, P.; and Saligrama, V. In Chaudhuri, K.; and Sugiyama, M., editor(s), The 22nd International Conference on Artificial Intelligence and Statistics, AISTATS 2019, 16-18 April 2019, Naha, Okinawa, Japan, volume 89, of Proceedings of Machine Learning Research, pages 2770–2779, 2019. PMLR
Cost aware Inference for IoT Devices [link]Paper   bibtex  
Online Algorithm for Unsupervised Sensor Selection. Verma, A.; Hanawal, M. K.; Szepesvári, C.; and Saligrama, V. In Chaudhuri, K.; and Sugiyama, M., editor(s), The 22nd International Conference on Artificial Intelligence and Statistics, AISTATS 2019, 16-18 April 2019, Naha, Okinawa, Japan, volume 89, of Proceedings of Machine Learning Research, pages 3168–3176, 2019. PMLR
Online Algorithm for Unsupervised Sensor Selection [link]Paper   bibtex  
Generalized Zero-Shot Recognition Based on Visually Semantic Embedding. Zhu, P.; Wang, H.; and Saligrama, V. In IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2019, Long Beach, CA, USA, June 16-20, 2019, pages 2995–3003, 2019. Computer Vision Foundation / IEEE
Generalized Zero-Shot Recognition Based on Visually Semantic Embedding [link]Paper   doi   bibtex  
Robust Text Classifier on Test-Time Budgets. Parvez, M. R.; Bolukbasi, T.; Chang, K.; and Saligrama, V. In Inui, K.; Jiang, J.; Ng, V.; and Wan, X., editor(s), Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, EMNLP-IJCNLP 2019, Hong Kong, China, November 3-7, 2019, pages 1167–1172, 2019. Association for Computational Linguistics
Robust Text Classifier on Test-Time Budgets [link]Paper   doi   bibtex  
Cost-Aware Fine-Grained Recognition for IoTs Based on Sequential Fixations. Wang, H.; Saligrama, V.; Sclaroff, S.; and Ablavsky, V. In 2019 IEEE/CVF International Conference on Computer Vision, ICCV 2019, Seoul, Korea (South), October 27 - November 2, 2019, pages 1252–1261, 2019. IEEE
Cost-Aware Fine-Grained Recognition for IoTs Based on Sequential Fixations [link]Paper   doi   bibtex  
Graph Resistance and Learning from Pairwise Comparisons. Hendrickx, J. M.; Olshevsky, A.; and Saligrama, V. In Chaudhuri, K.; and Salakhutdinov, R., editor(s), Proceedings of the 36th International Conference on Machine Learning, ICML 2019, 9-15 June 2019, Long Beach, California, USA, volume 97, of Proceedings of Machine Learning Research, pages 2702–2711, 2019. PMLR
Graph Resistance and Learning from Pairwise Comparisons [link]Paper   bibtex  
Learning Classifiers for Target Domain with Limited or No Labels. Zhu, P.; Wang, H.; and Saligrama, V. In Chaudhuri, K.; and Salakhutdinov, R., editor(s), Proceedings of the 36th International Conference on Machine Learning, ICML 2019, 9-15 June 2019, Long Beach, California, USA, volume 97, of Proceedings of Machine Learning Research, pages 7643–7653, 2019. PMLR
Learning Classifiers for Target Domain with Limited or No Labels [link]Paper   bibtex  
Efficient Near-Optimal Testing of Community Changes in Balanced Stochastic Block Models. Gangrade, A.; Venkatesh, P.; Nazer, B.; and Saligrama, V. In Wallach, H. M.; Larochelle, H.; Beygelzimer, A.; d'Alché-Buc , F.; Fox, E. B.; and Garnett, R., editor(s), Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada, pages 10364–10375, 2019.
Efficient Near-Optimal Testing of Community Changes in Balanced Stochastic Block Models [link]Paper   bibtex  
Shallow RNN: Accurate Time-series Classification on Resource Constrained Devices. Dennis, D. K.; Acar, D. A. E.; Mandikal, V.; Sadasivan, V. S.; Saligrama, V.; Simhadri, H. V.; and Jain, P. In Wallach, H. M.; Larochelle, H.; Beygelzimer, A.; d'Alché-Buc , F.; Fox, E. B.; and Garnett, R., editor(s), Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada, pages 12896–12906, 2019.
Shallow RNN: Accurate Time-series Classification on Resource Constrained Devices [link]Paper   bibtex  
Online Algorithm for Unsupervised Sensor Selection. Verma, A.; Hanawal, M. K.; Szepesvári, C.; and Saligrama, V. CoRR, abs/1901.04676. 2019.
Online Algorithm for Unsupervised Sensor Selection [link]Paper   bibtex  
Learning for New Visual Environments with Limited Labels. Zhu, P.; Wang, H.; and Saligrama, V. CoRR, abs/1901.09079. 2019.
Learning for New Visual Environments with Limited Labels [link]Paper   bibtex  
Graph Resistance and Learning from Pairwise Comparisons. Hendrickx, J. M.; Olshevsky, A.; and Saligrama, V. CoRR, abs/1902.00141. 2019.
Graph Resistance and Learning from Pairwise Comparisons [link]Paper   bibtex  
Equilibrated Recurrent Neural Network: Neuronal Time-Delayed Self-Feedback Improves Accuracy and Stability. Zhang, Z.; Kag, A.; Sullivan, A.; and Saligrama, V. CoRR, abs/1903.00755. 2019.
Equilibrated Recurrent Neural Network: Neuronal Time-Delayed Self-Feedback Improves Accuracy and Stability [link]Paper   bibtex  
Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers. Ma, Y.; Olshevsky, A.; Saligrama, V.; and Szepesvári, C. CoRR, abs/1904.11608. 2019.
Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers [link]Paper   bibtex  
Learning Bregman Divergences. Siahkamari, A.; Saligrama, V.; Castanon, D.; and Kulis, B. CoRR, abs/1905.11545. 2019.
Learning Bregman Divergences [link]Paper   bibtex  
RNNs Evolving on an Equilibrium Manifold: A Panacea for Vanishing and Exploding Gradients?. Kag, A.; Zhang, Z.; and Saligrama, V. CoRR, abs/1908.08574. 2019.
RNNs Evolving on an Equilibrium Manifold: A Panacea for Vanishing and Exploding Gradients? [link]Paper   bibtex  
Dont Even Look Once: Synthesizing Features for Zero-Shot Detection. Zhu, P.; Wang, H.; and Saligrama, V. CoRR, abs/1911.07933. 2019.
Dont Even Look Once: Synthesizing Features for Zero-Shot Detection [link]Paper   bibtex  
  2018 (8)
Sequential Optimization for Efficient High-Quality Object Proposal Generation. Zhang, Z.; Liu, Y.; Chen, X.; Zhu, Y.; Cheng, M.; Saligrama, V.; and Torr, P. H. S. IEEE Trans. Pattern Anal. Mach. Intell., 40(5): 1209–1223. 2018.
Sequential Optimization for Efficient High-Quality Object Proposal Generation [link]Paper   doi   bibtex  
On the Non-Existence of Unbiased Estimators in Constrained Estimation Problems. Somekh-Baruch, A.; Leshem, A.; and Saligrama, V. IEEE Trans. Inf. Theory, 64(8): 5549–5554. 2018.
On the Non-Existence of Unbiased Estimators in Constrained Estimation Problems [link]Paper   doi   bibtex  
Two-Sample Testing can be as Hard as Structure Learning in Ising Models: Minimax Lower Bounds. Gangrade, A.; Nazer, B.; and Saligrama, V. In 2018 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2018, Calgary, AB, Canada, April 15-20, 2018, pages 6931–6935, 2018. IEEE
Two-Sample Testing can be as Hard as Structure Learning in Ising Models: Minimax Lower Bounds [link]Paper   doi   bibtex  
Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers. Ma, Y.; Olshevsky, A.; Szepesvári, C.; and Saligrama, V. In Dy, J. G.; and Krause, A., editor(s), Proceedings of the 35th International Conference on Machine Learning, ICML 2018, Stockholmsmässan, Stockholm, Sweden, July 10-15, 2018, volume 80, of Proceedings of Machine Learning Research, pages 3341–3350, 2018. PMLR
Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers [link]Paper   bibtex  
Zero-Shot Detection. Zhu, P.; Wang, H.; Bolukbasi, T.; and Saligrama, V. CoRR, abs/1803.07113. 2018.
Zero-Shot Detection [link]Paper   bibtex  
Learning Where to Fixate on Foveated Images. Wang, H.; Saligrama, V.; Sclaroff, S.; and Ablavsky, V. CoRR, abs/1811.06868. 2018.
Learning Where to Fixate on Foveated Images [link]Paper   bibtex  
Generalized Zero-Shot Recognition based on Visually Semantic Embedding. Zhu, P.; Wang, H.; and Saligrama, V. CoRR, abs/1811.07993. 2018.
Generalized Zero-Shot Recognition based on Visually Semantic Embedding [link]Paper   bibtex  
Testing Changes in Communities for the Stochastic Block Model. Gangrade, A.; Venkatesh, P.; Nazer, B.; and Saligrama, V. CoRR, abs/1812.00769. 2018.
Testing Changes in Communities for the Stochastic Block Model [link]Paper   bibtex  
  2017 (20)
PRISM: Person Reidentification via Structured Matching. Zhang, Z.; and Saligrama, V. IEEE Trans. Circuits Syst. Video Technol., 27(3): 499–512. 2017.
PRISM: Person Reidentification via Structured Matching [link]Paper   doi   bibtex  
Sparse Signal Processing With Linear and Nonlinear Observations: A Unified Shannon-Theoretic Approach. Aksoylar, C.; Atia, G. K.; and Saligrama, V. IEEE Trans. Inf. Theory, 63(2): 749–776. 2017.
Sparse Signal Processing With Linear and Nonlinear Observations: A Unified Shannon-Theoretic Approach [link]Paper   doi   bibtex  
Learning Immune-Defectives Graph Through Group Tests. Ganesan, A.; Jaggi, S.; and Saligrama, V. IEEE Trans. Inf. Theory, 63(5): 3010–3028. 2017.
Learning Immune-Defectives Graph Through Group Tests [link]Paper   doi   bibtex  
Comments on the Proof of Adaptive Stochastic Set Cover Based on Adaptive Submodularity and Its Implications for the Group Identification Problem in "Group-Based Active Query Selection for Rapid Diagnosis in Time-Critical Situations". Nan, F.; and Saligrama, V. IEEE Trans. Inf. Theory, 63(11): 7612–7614. 2017.
Comments on the Proof of Adaptive Stochastic Set Cover Based on Adaptive Submodularity and Its Implications for the Group Identification Problem in "Group-Based Active Query Selection for Rapid Diagnosis in Time-Critical Situations" [link]Paper   doi   bibtex  
Clustering and Community Detection With Imbalanced Clusters. Aksoylar, C.; Qian, J.; and Saligrama, V. IEEE Trans. Signal Inf. Process. over Networks, 3(1): 61–76. 2017.
Clustering and Community Detection With Imbalanced Clusters [link]Paper   doi   bibtex  
Resource Constrained Structured Prediction. Bolukbasi, T.; Chang, K.; Wang, J.; and Saligrama, V. In Singh, S. P.; and Markovitch, S., editor(s), Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, February 4-9, 2017, San Francisco, California, USA, pages 1756–1762, 2017. AAAI Press
Resource Constrained Structured Prediction [link]Paper   bibtex  
Unsupervised Sequential Sensor Acquisition. Hanawal, M. K.; Szepesvári, C.; and Saligrama, V. In Singh, A.; and Zhu, X. (., editor(s), Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, AISTATS 2017, 20-22 April 2017, Fort Lauderdale, FL, USA, volume 54, of Proceedings of Machine Learning Research, pages 803–811, 2017. PMLR
Unsupervised Sequential Sensor Acquisition [link]Paper   bibtex  
Lower bounds for two-sample structural change detection in ising and Gaussian models. Gangrade, A.; Nazer, B.; and Saligrama, V. In 55th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2017, Monticello, IL, USA, October 3-6, 2017, pages 1016–1025, 2017. IEEE
Lower bounds for two-sample structural change detection in ising and Gaussian models [link]Paper   doi   bibtex  
Connected Subgraph Detection with Mirror Descent on SDPs. Aksoylar, C.; Orecchia, L.; and Saligrama, V. In Precup, D.; and Teh, Y. W., editor(s), Proceedings of the 34th International Conference on Machine Learning, ICML 2017, Sydney, NSW, Australia, 6-11 August 2017, volume 70, of Proceedings of Machine Learning Research, pages 51–59, 2017. PMLR
Connected Subgraph Detection with Mirror Descent on SDPs [link]Paper   bibtex  
Adaptive Neural Networks for Efficient Inference. Bolukbasi, T.; Wang, J.; Dekel, O.; and Saligrama, V. In Precup, D.; and Teh, Y. W., editor(s), Proceedings of the 34th International Conference on Machine Learning, ICML 2017, Sydney, NSW, Australia, 6-11 August 2017, volume 70, of Proceedings of Machine Learning Research, pages 527–536, 2017. PMLR
Adaptive Neural Networks for Efficient Inference [link]Paper   bibtex  
Adaptive Classification for Prediction Under a Budget. Nan, F.; and Saligrama, V. In Guyon, I.; von Luxburg, U.; Bengio, S.; Wallach, H. M.; Fergus, R.; Vishwanathan, S. V. N.; and Garnett, R., editor(s), Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, December 4-9, 2017, Long Beach, CA, USA, pages 4727–4737, 2017.
Adaptive Classification for Prediction Under a Budget [link]Paper   bibtex  
Adaptive Neural Networks for Fast Test-Time Prediction. Bolukbasi, T.; Wang, J.; Dekel, O.; and Saligrama, V. CoRR, abs/1702.07811. 2017.
Adaptive Neural Networks for Fast Test-Time Prediction [link]Paper   bibtex  
Field of Groves: An Energy-Efficient Random Forest. Takhirov, Z.; Wang, J.; Louis, M. S.; Saligrama, V.; and Joshi, A. CoRR, abs/1704.02978. 2017.
Field of Groves: An Energy-Efficient Random Forest [link]Paper   bibtex  
Dynamic Model Selection for Prediction Under a Budget. Nan, F.; and Saligrama, V. CoRR, abs/1704.07505. 2017.
Dynamic Model Selection for Prediction Under a Budget [link]Paper   bibtex  
Comments on the proof of adaptive submodular function minimization. Nan, F.; and Saligrama, V. CoRR, abs/1705.03771. 2017.
Comments on the proof of adaptive submodular function minimization [link]Paper   bibtex  
Adaptive Classification for Prediction Under a Budget. Nan, F.; and Saligrama, V. CoRR, abs/1705.10194. 2017.
Adaptive Classification for Prediction Under a Budget [link]Paper   bibtex  
Sequential Dynamic Decision Making with Deep Neural Nets on a Test-Time Budget. Zhu, H.; Nan, F.; Paschalidis, I. C.; and Saligrama, V. CoRR, abs/1705.10924. 2017.
Sequential Dynamic Decision Making with Deep Neural Nets on a Test-Time Budget [link]Paper   bibtex  
Crowdsourcing with Sparsely Interacting Workers. Ma, Y.; Olshevsky, A.; Saligrama, V.; and Szepesvári, C. CoRR, abs/1706.06660. 2017.
Crowdsourcing with Sparsely Interacting Workers [link]Paper   bibtex  
Lower Bounds for Two-Sample Structural Change Detection in Ising and Gaussian Models. Gangrade, A.; Nazer, B.; and Saligrama, V. CoRR, abs/1710.10366. 2017.
Lower Bounds for Two-Sample Structural Change Detection in Ising and Gaussian Models [link]Paper   bibtex  
Probabilistic Semantic Retrieval for Surveillance Videos with Activity Graphs. Chen, Y.; Wang, J.; Bai, Y.; Castañón, G. D.; and Saligrama, V. CoRR, abs/1712.06204. 2017.
Probabilistic Semantic Retrieval for Surveillance Videos with Activity Graphs [link]Paper   bibtex  
  2016 (22)
A Provably Efficient Algorithm for Separable Topic Discovery. Ding, W.; Ishwar, P.; and Saligrama, V. IEEE J. Sel. Top. Signal Process., 10(4): 712–725. 2016.
A Provably Efficient Algorithm for Separable Topic Discovery [link]Paper   doi   bibtex  
Retrieval in Long-Surveillance Videos Using User-Described Motion and Object Attributes. Castañón, G.; Elgharib, M. A.; Saligrama, V.; and Jodoin, P. IEEE Trans. Circuits Syst. Video Technol., 26(12): 2313–2327. 2016.
Retrieval in Long-Surveillance Videos Using User-Described Motion and Object Attributes [link]Paper   doi   bibtex  
Guest Editorial Inference and Learning over Networks. Matta, V.; Richard, C.; Saligrama, V.; and Sayed, A. H. IEEE Trans. Signal Inf. Process. over Networks, 2(4): 423–425. 2016.
Guest Editorial Inference and Learning over Networks [link]Paper   doi   bibtex  
Minimax Optimal Sparse Signal Recovery With Poisson Statistics. Rohban, M. H.; Saligrama, V.; and Vaziri, D. M. IEEE Trans. Signal Process., 64(13): 3495–3508. 2016.
Minimax Optimal Sparse Signal Recovery With Poisson Statistics [link]Paper   doi   bibtex  
A multi-resolution approach for discovery and 3-D modeling of archaeological sites using satellite imagery and a UAV-borne camera. Ding, H.; Cristofalo, E.; Wang, J.; Castañón, D. A.; Montijano, E.; Saligrama, V.; and Schwager, M. In 2016 American Control Conference, ACC 2016, Boston, MA, USA, July 6-8, 2016, pages 1359–1365, 2016. IEEE
A multi-resolution approach for discovery and 3-D modeling of archaeological sites using satellite imagery and a UAV-borne camera [link]Paper   doi   bibtex  
Efficient Training of Very Deep Neural Networks for Supervised Hashing. Zhang, Z.; Chen, Y.; and Saligrama, V. In 2016 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016, Las Vegas, NV, USA, June 27-30, 2016, pages 1487–1495, 2016. IEEE Computer Society
Efficient Training of Very Deep Neural Networks for Supervised Hashing [link]Paper   doi   bibtex  
Zero-Shot Learning via Joint Latent Similarity Embedding. Zhang, Z.; and Saligrama, V. In 2016 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016, Las Vegas, NV, USA, June 27-30, 2016, pages 6034–6042, 2016. IEEE Computer Society
Zero-Shot Learning via Joint Latent Similarity Embedding [link]Paper   doi   bibtex  
Zero-Shot Recognition via Structured Prediction. Zhang, Z.; and Saligrama, V. In Leibe, B.; Matas, J.; Sebe, N.; and Welling, M., editor(s), Computer Vision - ECCV 2016 - 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part VII, volume 9911, of Lecture Notes in Computer Science, pages 533–548, 2016. Springer
Zero-Shot Recognition via Structured Prediction [link]Paper   doi   bibtex  
Efficient algorithms for linear polyhedral bandits. Hanawal, M. K.; Leshem, A.; and Saligrama, V. In 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016, Shanghai, China, March 20-25, 2016, pages 4796–4800, 2016. IEEE
Efficient algorithms for linear polyhedral bandits [link]Paper   doi   bibtex  
Energy-Efficient Adaptive Classifier Design for Mobile Systems. Takhirov, Z.; Wang, J.; Saligrama, V.; and Joshi, A. In Proceedings of the 2016 International Symposium on Low Power Electronics and Design, ISLPED 2016, San Francisco Airport, CA, USA, August 08 - 10, 2016, pages 52–57, 2016. ACM
Energy-Efficient Adaptive Classifier Design for Mobile Systems [link]Paper   doi   bibtex  
Pruning Random Forests for Prediction on a Budget. Nan, F.; Wang, J.; and Saligrama, V. In Lee, D. D.; Sugiyama, M.; von Luxburg, U.; Guyon, I.; and Garnett, R., editor(s), Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, December 5-10, 2016, Barcelona, Spain, pages 2334–2342, 2016.
Pruning Random Forests for Prediction on a Budget [link]Paper   bibtex  
Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings. Bolukbasi, T.; Chang, K.; Zou, J. Y.; Saligrama, V.; and Kalai, A. T. In Lee, D. D.; Sugiyama, M.; von Luxburg, U.; Guyon, I.; and Garnett, R., editor(s), Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, December 5-10, 2016, Barcelona, Spain, pages 4349–4357, 2016.
Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings [link]Paper   bibtex  
Optimally Pruning Decision Tree Ensembles With Feature Cost. Nan, F.; Wang, J.; and Saligrama, V. CoRR, abs/1601.00955. 2016.
Optimally Pruning Decision Tree Ensembles With Feature Cost [link]Paper   bibtex  
Learning Minimum Volume Sets and Anomaly Detectors from KNN Graphs. Root, J.; Saligrama, V.; and Qian, J. CoRR, abs/1601.06105. 2016.
Learning Minimum Volume Sets and Anomaly Detectors from KNN Graphs [link]Paper   bibtex  
Structured Prediction with Test-time Budget Constraints. Bolukbasi, T.; Chang, K.; Wang, J.; and Saligrama, V. CoRR, abs/1602.08761. 2016.
Structured Prediction with Test-time Budget Constraints [link]Paper   bibtex  
Pruning Random Forests for Prediction on a Budget. Nan, F.; Wang, J.; and Saligrama, V. CoRR, abs/1606.05060. 2016.
Pruning Random Forests for Prediction on a Budget [link]Paper   bibtex  
Quantifying and Reducing Stereotypes in Word Embeddings. Bolukbasi, T.; Chang, K.; Zou, J. Y.; Saligrama, V.; and Kalai, A. T. CoRR, abs/1606.06121. 2016.
Quantifying and Reducing Stereotypes in Word Embeddings [link]Paper   bibtex  
Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings. Bolukbasi, T.; Chang, K.; Zou, J. Y.; Saligrama, V.; and Kalai, A. CoRR, abs/1607.06520. 2016.
Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings [link]Paper   bibtex  
Clustering and Community Detection with Imbalanced Clusters. Aksoylar, C.; Qian, J.; and Saligrama, V. CoRR, abs/1608.07605. 2016.
Clustering and Community Detection with Imbalanced Clusters [link]Paper   bibtex  
On the Non-Existence of Unbiased Estimators in Constrained Estimation Problems. Somekh-Baruch, A.; Leshem, A.; and Saligrama, V. CoRR, abs/1609.07415. 2016.
On the Non-Existence of Unbiased Estimators in Constrained Estimation Problems [link]Paper   bibtex  
Sequential Learning without Feedback. Hanawal, M. K.; Szepesvári, C.; and Saligrama, V. CoRR, abs/1610.05394. 2016.
Sequential Learning without Feedback [link]Paper   bibtex  
Learning Joint Feature Adaptation for Zero-Shot Recognition. Zhang, Z.; and Saligrama, V. CoRR, abs/1611.07593. 2016.
Learning Joint Feature Adaptation for Zero-Shot Recognition [link]Paper   bibtex  
  2015 (32)
Prediction of hospitalization due to heart diseases by supervised learning methods. Dai, W.; Brisimi, T. S.; Adams, W. G.; Mela, T.; Saligrama, V.; and Paschalidis, I. C. Int. J. Medical Informatics, 84(3): 189–197. 2015.
Prediction of hospitalization due to heart diseases by supervised learning methods [link]Paper   doi   bibtex  
Correction to "Boolean Compressed Sensing and Noisy Group Testing". Atia, G. K.; Saligrama, V.; and Aksoylar, C. IEEE Trans. Inf. Theory, 61(3): 1507. 2015.
Correction to "Boolean Compressed Sensing and Noisy Group Testing" [link]Paper   doi   bibtex  
A Topic Modeling Approach to Ranking. Ding, W.; Ishwar, P.; and Saligrama, V. In Lebanon, G.; and Vishwanathan, S. V. N., editor(s), Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, AISTATS 2015, San Diego, California, USA, May 9-12, 2015, volume 38, of JMLR Workshop and Conference Proceedings, 2015. JMLR.org
A Topic Modeling Approach to Ranking [link]Paper   bibtex  
Learning Efficient Anomaly Detectors from K-NN Graphs. Root, J.; Qian, J.; and Saligrama, V. In Lebanon, G.; and Vishwanathan, S. V. N., editor(s), Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, AISTATS 2015, San Diego, California, USA, May 9-12, 2015, volume 38, of JMLR Workshop and Conference Proceedings, 2015. JMLR.org
Learning Efficient Anomaly Detectors from K-NN Graphs [link]Paper   bibtex  
Cost effective algorithms for spectral bandits. Hanawal, M. K.; and Saligrama, V. In 53rd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2015, Allerton Park & Retreat Center, Monticello, IL, USA, September 29 - October 2, 2015, pages 1323–1329, 2015. IEEE
Cost effective algorithms for spectral bandits [link]Paper   doi   bibtex  
Rapid: Rapidly accelerated proximal gradient algorithms for convex minimization. Zhang, Z.; and Saligrama, V. In 2015 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2015, South Brisbane, Queensland, Australia, April 19-24, 2015, pages 3796–3800, 2015. IEEE
Rapid: Rapidly accelerated proximal gradient algorithms for convex minimization [link]Paper   doi   bibtex  
Learning shared rankings from mixtures of noisy pairwise comparisons. Ding, W.; Ishwar, P.; and Saligrama, V. In 2015 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2015, South Brisbane, Queensland, Australia, April 19-24, 2015, pages 5446–5450, 2015. IEEE
Learning shared rankings from mixtures of noisy pairwise comparisons [link]Paper   doi   bibtex  
Efficient detection and localization on graph structured data. Hanawal, M. K.; and Saligrama, V. In 2015 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2015, South Brisbane, Queensland, Australia, April 19-24, 2015, pages 5590–5594, 2015. IEEE
Efficient detection and localization on graph structured data [link]Paper   doi   bibtex  
Group Membership Prediction. Zhang, Z.; Chen, Y.; and Saligrama, V. In 2015 IEEE International Conference on Computer Vision, ICCV 2015, Santiago, Chile, December 7-13, 2015, pages 3916–3924, 2015. IEEE Computer Society
Group Membership Prediction [link]Paper   doi   bibtex  
Zero-Shot Learning via Semantic Similarity Embedding. Zhang, Z.; and Saligrama, V. In 2015 IEEE International Conference on Computer Vision, ICCV 2015, Santiago, Chile, December 7-13, 2015, pages 4166–4174, 2015. IEEE Computer Society
Zero-Shot Learning via Semantic Similarity Embedding [link]Paper   doi   bibtex  
Feature-Budgeted Random Forest. Nan, F.; Wang, J.; and Saligrama, V. In Bach, F. R.; and Blei, D. M., editor(s), Proceedings of the 32nd International Conference on Machine Learning, ICML 2015, Lille, France, 6-11 July 2015, volume 37, of JMLR Workshop and Conference Proceedings, pages 1983–1991, 2015. JMLR.org
Feature-Budgeted Random Forest [link]Paper   bibtex  
Cheap Bandits. Hanawal, M. K.; Saligrama, V.; Valko, M.; and Munos, R. In Bach, F. R.; and Blei, D. M., editor(s), Proceedings of the 32nd International Conference on Machine Learning, ICML 2015, Lille, France, 6-11 July 2015, volume 37, of JMLR Workshop and Conference Proceedings, pages 2133–2142, 2015. JMLR.org
Cheap Bandits [link]Paper   bibtex  
Learning immune-defectives graph through group tests. Ganesan, A.; Jaggi, S.; and Saligrama, V. In IEEE International Symposium on Information Theory, ISIT 2015, Hong Kong, China, June 14-19, 2015, pages 66–70, 2015. IEEE
Learning immune-defectives graph through group tests [link]Paper   doi   bibtex  
Most large topic models are approximately separable. Ding, W.; Ishwar, P.; and Saligrama, V. In 2015 Information Theory and Applications Workshop, ITA 2015, San Diego, CA, USA, February 1-6, 2015, pages 199–203, 2015. IEEE
Most large topic models are approximately separable [link]Paper   doi   bibtex  
Non-adaptive group testing with inhibitors. Ganesan, A.; Jaggi, S.; and Saligrama, V. In 2015 IEEE Information Theory Workshop, ITW 2015, Jerusalem, Israel, April 26 - May 1, 2015, pages 1–5, 2015. IEEE
Non-adaptive group testing with inhibitors [link]Paper   doi   bibtex  
Efficient Activity Retrieval through Semantic Graph Queries. Castañón, G. D.; Chen, Y.; Zhang, Z.; and Saligrama, V. In Zhou, X.; Smeaton, A. F.; Tian, Q.; Bulterman, D. C. A.; Shen, H. T.; Mayer-Patel, K.; and Yan, S., editor(s), Proceedings of the 23rd Annual ACM Conference on Multimedia Conference, MM '15, Brisbane, Australia, October 26 - 30, 2015, pages 391–400, 2015. ACM
Efficient Activity Retrieval through Semantic Graph Queries [link]Paper   doi   bibtex  
Efficient Learning by Directed Acyclic Graph For Resource Constrained Prediction. Wang, J.; Trapeznikov, K.; and Saligrama, V. In Cortes, C.; Lawrence, N. D.; Lee, D. D.; Sugiyama, M.; and Garnett, R., editor(s), Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, December 7-12, 2015, Montreal, Quebec, Canada, pages 2152–2160, 2015.
Efficient Learning by Directed Acyclic Graph For Resource Constrained Prediction [link]Paper   bibtex  
Max-Cost Discrete Function Evaluation Problem under a Budget. Nan, F.; Wang, J.; and Saligrama, V. CoRR, abs/1501.02702. 2015.
Max-Cost Discrete Function Evaluation Problem under a Budget [link]Paper   bibtex  
Learning Efficient Anomaly Detectors from K-NN Graphs. Qian, J.; Root, J.; and Saligrama, V. CoRR, abs/1502.01783. 2015.
Learning Efficient Anomaly Detectors from K-NN Graphs [link]Paper   bibtex  
Feature-Budgeted Random Forest. Nan, F.; Wang, J.; and Saligrama, V. CoRR, abs/1502.05925. 2015.
Feature-Budgeted Random Forest [link]Paper   bibtex  
Learning Immune-Defectives Graph through Group Tests. Ganesan, A.; Jaggi, S.; and Saligrama, V. CoRR, abs/1503.00555. 2015.
Learning Immune-Defectives Graph through Group Tests [link]Paper   bibtex  
Learning Mixed Membership Mallows Models from Pairwise Comparisons. Ding, W.; Ishwar, P.; and Saligrama, V. CoRR, abs/1504.00757. 2015.
Learning Mixed Membership Mallows Models from Pairwise Comparisons [link]Paper   bibtex  
Cheap Bandits. Hanawal, M. K.; Saligrama, V.; Valko, M.; and Munos, R. CoRR, abs/1506.04782. 2015.
Cheap Bandits [link]Paper   bibtex  
Necessary and Sufficient Conditions and a Provably Efficient Algorithm for Separable Topic Discovery. Ding, W.; Ishwar, P.; and Saligrama, V. CoRR, abs/1508.05565. 2015.
Necessary and Sufficient Conditions and a Provably Efficient Algorithm for Separable Topic Discovery [link]Paper   bibtex  
Sensor Selection by Linear Programming. Wang, J.; Trapeznikov, K.; and Saligrama, V. CoRR, abs/1509.02954. 2015.
Sensor Selection by Linear Programming [link]Paper   bibtex  
Zero-Shot Learning via Semantic Similarity Embedding. Zhang, Z.; and Saligrama, V. CoRR, abs/1509.04767. 2015.
Zero-Shot Learning via Semantic Similarity Embedding [link]Paper   bibtex  
Group Membership Prediction. Zhang, Z.; Chen, Y.; and Saligrama, V. CoRR, abs/1509.04783. 2015.
Group Membership Prediction [link]Paper   bibtex  
Algorithms for Linear Bandits on Polyhedral Sets. Hanawal, M. K.; Leshem, A.; and Saligrama, V. CoRR, abs/1509.07927. 2015.
Algorithms for Linear Bandits on Polyhedral Sets [link]Paper   bibtex  
Efficient Learning by Directed Acyclic Graph For Resource Constrained Prediction. Wang, J.; Trapeznikov, K.; and Saligrama, V. CoRR, abs/1510.07609. 2015.
Efficient Learning by Directed Acyclic Graph For Resource Constrained Prediction [link]Paper   bibtex  
BING++: A Fast High Quality Object Proposal Generator at 100fps. Zhang, Z.; Liu, Y.; Bolukbasi, T.; Cheng, M.; and Saligrama, V. CoRR, abs/1511.04511. 2015.
BING++: A Fast High Quality Object Proposal Generator at 100fps [link]Paper   bibtex  
Classifying Unseen Instances by Learning Class-Independent Similarity Functions. Zhang, Z.; and Saligrama, V. CoRR, abs/1511.04512. 2015.
Classifying Unseen Instances by Learning Class-Independent Similarity Functions [link]Paper   bibtex  
Supervised Hashing with Deep Neural Networks. Zhang, Z.; Chen, Y.; and Saligrama, V. CoRR, abs/1511.04524. 2015.
Supervised Hashing with Deep Neural Networks [link]Paper   bibtex  
  2014 (22)
Non-Adaptive Group Testing: Explicit Bounds and Novel Algorithms. Chan, C. L.; Jaggi, S.; Saligrama, V.; and Agnihotri, S. IEEE Trans. Inf. Theory, 60(5): 3019–3035. 2014.
Non-Adaptive Group Testing: Explicit Bounds and Novel Algorithms [link]Paper   doi   bibtex  
Information-Theoretic Characterization of Sparse Recovery. Aksoylar, C.; and Saligrama, V. In Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, AISTATS 2014, Reykjavik, Iceland, April 22-25, 2014, volume 33, of JMLR Workshop and Conference Proceedings, pages 38–46, 2014. JMLR.org
Information-Theoretic Characterization of Sparse Recovery [link]Paper   bibtex  
Efficient Distributed Topic Modeling with Provable Guarantees. Ding, W.; Rohban, M. H.; Ishwar, P.; and Saligrama, V. In Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, AISTATS 2014, Reykjavik, Iceland, April 22-25, 2014, volume 33, of JMLR Workshop and Conference Proceedings, pages 167–175, 2014. JMLR.org
Efficient Distributed Topic Modeling with Provable Guarantees [link]Paper   bibtex  
Connected Sub-graph Detection. Qian, J.; Saligrama, V.; and Chen, Y. In Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, AISTATS 2014, Reykjavik, Iceland, April 22-25, 2014, volume 33, of JMLR Workshop and Conference Proceedings, pages 796–804, 2014. JMLR.org
Connected Sub-graph Detection [link]Paper   bibtex  
An LP for Sequential Learning Under Budgets. Wang, J.; Trapeznikov, K.; and Saligrama, V. In Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, AISTATS 2014, Reykjavik, Iceland, April 22-25, 2014, volume 33, of JMLR Workshop and Conference Proceedings, pages 987–995, 2014. JMLR.org
An LP for Sequential Learning Under Budgets [link]Paper   bibtex  
A Novel Visual Word Co-occurrence Model for Person Re-identification. Zhang, Z.; Chen, Y.; and Saligrama, V. In Agapito, L.; Bronstein, M. M.; and Rother, C., editor(s), Computer Vision - ECCV 2014 Workshops - Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part III, volume 8927, of Lecture Notes in Computer Science, pages 122–133, 2014. Springer
A Novel Visual Word Co-occurrence Model for Person Re-identification [link]Paper   doi   bibtex  
Model Selection by Linear Programming. Wang, J.; Bolukbasi, T.; Trapeznikov, K.; and Saligrama, V. In Fleet, D. J.; Pajdla, T.; Schiele, B.; and Tuytelaars, T., editor(s), Computer Vision - ECCV 2014 - 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part II, volume 8690, of Lecture Notes in Computer Science, pages 647–662, 2014. Springer
Model Selection by Linear Programming [link]Paper   doi   bibtex  
Sensing-aware kernel SVM. Ding, W.; Ishwar, P.; Saligrama, V.; and Karl, W. C. In IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2014, Florence, Italy, May 4-9, 2014, pages 2947–2951, 2014. IEEE
Sensing-aware kernel SVM [link]Paper   doi   bibtex  
Fast margin-based cost-sensitive classification. Nan, F.; Wang, J.; Trapeznikov, K.; and Saligrama, V. In IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2014, Florence, Italy, May 4-9, 2014, pages 2952–2956, 2014. IEEE
Fast margin-based cost-sensitive classification [link]Paper   doi   bibtex  
Spectral clustering with imbalanced data. Qian, J.; and Saligrama, V. In IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2014, Florence, Italy, May 4-9, 2014, pages 3057–3061, 2014. IEEE
Spectral clustering with imbalanced data [link]Paper   doi   bibtex  
Anomalous cluster detection. Qian, J.; Saligrama, V.; and Chen, Y. In IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2014, Florence, Italy, May 4-9, 2014, pages 3854–3858, 2014. IEEE
Anomalous cluster detection [link]Paper   doi   bibtex  
Sparse signal recovery under poisson statistics for online marketing applications. Motamedvaziri, D.; Rohban, M. H.; and Saligrama, V. In IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2014, Florence, Italy, May 4-9, 2014, pages 4953–4957, 2014. IEEE
Sparse signal recovery under poisson statistics for online marketing applications [link]Paper   doi   bibtex  
Information-theoretic bounds for adaptive sparse recovery. Aksoylar, C.; and Saligrama, V. In 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29 - July 4, 2014, pages 1311–1315, 2014. IEEE
Information-theoretic bounds for adaptive sparse recovery [link]Paper   doi   bibtex  
Efficient Minimax Signal Detection on Graphs. Qian, J.; and Saligrama, V. In Ghahramani, Z.; Welling, M.; Cortes, C.; Lawrence, N. D.; and Weinberger, K. Q., editor(s), Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, December 8-13 2014, Montreal, Quebec, Canada, pages 2708–2716, 2014.
Efficient Minimax Signal Detection on Graphs [link]Paper   bibtex  
Information-Theoretic Bounds for Adaptive Sparse Recovery. Aksoylar, C.; and Saligrama, V. CoRR, abs/1402.5731. 2014.
Information-Theoretic Bounds for Adaptive Sparse Recovery [link]Paper   bibtex  
Sparse Recovery with Linear and Nonlinear Observations: Dependent and Noisy Data. Aksoylar, C.; and Saligrama, V. CoRR, abs/1403.3109. 2014.
Sparse Recovery with Linear and Nonlinear Observations: Dependent and Noisy Data [link]Paper   bibtex  
Retrieval in Long Surveillance Videos using User Described Motion and Object Attributes. Castañón, G.; Elgharib, M. A.; Saligrama, V.; and Jodoin, P. CoRR, abs/1405.0234. 2014.
Retrieval in Long Surveillance Videos using User Described Motion and Object Attributes [link]Paper   bibtex  
Person Re-identification via Structured Prediction. Zhang, Z.; and Saligrama, V. CoRR, abs/1406.4444. 2014.
Person Re-identification via Structured Prediction [link]Paper   bibtex  
RAPID: Rapidly Accelerated Proximal Gradient Algorithms for Convex Minimization. Zhang, Z.; and Saligrama, V. CoRR, abs/1406.4445. 2014.
RAPID: Rapidly Accelerated Proximal Gradient Algorithms for Convex Minimization [link]Paper   bibtex  
A Novel Visual Word Co-occurrence Model for Person Re-identification. Zhang, Z.; Chen, Y.; and Saligrama, V. CoRR, abs/1410.6532. 2014.
A Novel Visual Word Co-occurrence Model for Person Re-identification [link]Paper   bibtex  
Non-Adaptive Group Testing with Inhibitors. Ganesan, A.; Ebrahimi, J.; Jaggi, S.; and Saligrama, V. CoRR, abs/1410.8440. 2014.
Non-Adaptive Group Testing with Inhibitors [link]Paper   bibtex  
A Topic Modeling Approach to Ranking. Ding, W.; Ishwar, P.; and Saligrama, V. CoRR, abs/1412.3705. 2014.
A Topic Modeling Approach to Ranking [link]Paper   bibtex  
  2013 (20)
Introduction to the issue on anomalous pattern discovery for spatial, temporal, networked, and high-dimensional signals. Saligrama, V.; Arias-Castro, E.; Chellappa, R.; III, A. O. H.; Nowak, R. D.; and Veeravalli, V. V. IEEE J. Sel. Top. Signal Process., 7(1): 1–3. 2013.
Introduction to the issue on anomalous pattern discovery for spatial, temporal, networked, and high-dimensional signals [link]Paper   doi   bibtex  
Multi-stage classifier design. Trapeznikov, K.; Saligrama, V.; and Castañón, D. A. Mach. Learn., 92(2-3): 479–502. 2013.
Multi-stage classifier design [link]Paper   doi   bibtex  
Locally-Linear Learning Machines (L3M). Wang, J.; and Saligrama, V. In Ong, C. S.; and Ho, T. B., editor(s), Asian Conference on Machine Learning, ACML 2013, Canberra, ACT, Australia, November 13-15, 2013, volume 29, of JMLR Workshop and Conference Proceedings, pages 451–466, 2013. JMLR.org
Locally-Linear Learning Machines (L3M) [link]Paper   bibtex  
Dynamic topic discovery through sequential projections. Ding, W.; Ishwar, P.; and Saligrama, V. In Matthews, M. B., editor(s), 2013 Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, USA, November 3-6, 2013, pages 1100–1104, 2013. IEEE
Dynamic topic discovery through sequential projections [link]Paper   doi   bibtex  
Supervised Sequential Classification Under Budget Constraints. Trapeznikov, K.; and Saligrama, V. In Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, AISTATS 2013, Scottsdale, AZ, USA, April 29 - May 1, 2013, volume 31, of JMLR Workshop and Conference Proceedings, pages 581–589, 2013. JMLR.org
Supervised Sequential Classification Under Budget Constraints [link]Paper   bibtex  
Sparse signal recovery under Poisson statistics. Motamedvaziri, D.; Rohban, M. H.; and Saligrama, V. In 51st Annual Allerton Conference on Communication, Control, and Computing, Allerton 2013, Allerton Park & Retreat Center, Monticello, IL, USA, October 2-4, 2013, pages 1450–1457, 2013. IEEE
Sparse signal recovery under Poisson statistics [link]Paper   doi   bibtex  
Online local linear classification. Wang, J.; Trapeznikov, K.; and Saligrama, V. In 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2013, St. Martin, France, December 15-18, 2013, pages 173–176, 2013. IEEE
Online local linear classification [link]Paper   doi   bibtex  
User-assisted reflection detection and feature point tracking. Elgharib, M. A.; Pitié, F.; Kokaram, A. C.; and Saligrama, V. In Kokaram, A. C.; and Hall, P., editor(s), Conference on Visual Media Production 2013, CVMP '13, London, United Kingdom, November 6-7, 2013, pages 13:1–13:10, 2013. ACM
User-assisted reflection detection and feature point tracking [link]Paper   doi   bibtex  
A new one-class SVM for anomaly detection. Chen, Y.; Qian, J.; and Saligrama, V. In IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2013, Vancouver, BC, Canada, May 26-31, 2013, pages 3567–3571, 2013. IEEE
A new one-class SVM for anomaly detection [link]Paper   doi   bibtex  
Compressive sensing bounds through a unifying framework for sparse models. Aksoylar, C.; Atia, G. K.; and Saligrama, V. In IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2013, Vancouver, BC, Canada, May 26-31, 2013, pages 5524–5528, 2013. IEEE
Compressive sensing bounds through a unifying framework for sparse models [link]Paper   doi   bibtex  
A new geometric approach to latent topic modeling and discovery. Ding, W.; Rohban, M. H.; Ishwar, P.; and Saligrama, V. In IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2013, Vancouver, BC, Canada, May 26-31, 2013, pages 5568–5572, 2013. IEEE
A new geometric approach to latent topic modeling and discovery [link]Paper   doi   bibtex  
Topic Discovery through Data Dependent and Random Projections. Ding, W.; Rohban, M. H.; Ishwar, P.; and Saligrama, V. In Proceedings of the 30th International Conference on Machine Learning, ICML 2013, Atlanta, GA, USA, 16-21 June 2013, volume 28, of JMLR Workshop and Conference Proceedings, pages 1202–1210, 2013. JMLR.org
Topic Discovery through Data Dependent and Random Projections [link]Paper   bibtex  
Sparse signal processing with linear and non-linear observations: A unified shannon theoretic approach. Aksoylar, C.; Atia, G. K.; and Saligrama, V. In 2013 IEEE Information Theory Workshop, ITW 2013, Sevilla, Spain, September 9-13, 2013, pages 1–5, 2013. IEEE
Sparse signal processing with linear and non-linear observations: A unified shannon theoretic approach [link]Paper   doi   bibtex