1. 1.Raman Arora, Michael Dinitz, Teodor V. Marinov, and Mehryar Mohri. Policy Regret in Repeated Games. Advances in Neural Information Processing Systems (NIPS), 2018 [pdf].

1. 2.Raman Arora, Vladimir Braverman, and Jalaj Upadhyay. Differentially Private Robust PCA. Advances in Neural Information Processing Systems (NIPS), 2018 [pdf].

1. 3.Enayat M. Ullah, Poorya Mianjy, Teodor V. Marinov, and Raman Arora. Streaming Kernel PCA with $\tilde{O}(\sqrt{n})$ Random Features. Advances in Neural Information Processing Systems (NIPS), 2018 [pdf].

1. 4.Lin F. Yang, Raman Arora, Vladimir Braverman, and Tuo Zhao. The Physical Systems Behind Optimization Algorithms. Advances in Neural Information Processing Systems (NIPS), 2018 [pdf].

1. 5.Poorya Mianjy, Raman Arora and Rene Vidal. On the Implicit Bias of Dropout. In Proceedings of the 35th International Conference on Machine Learning (ICML), 2018 [pdf].

1. 6.Poorya Mianjy and Raman Arora. Stochastic PCA with l1 and l2 regularization. In Proceedings of the 35th International Conference on Machine Learning (ICML), 2018 [pdf].

1. 7.Teodor V. Marinov, Poorya Mianjy, Raman Arora. Streaming PCA in noisy settings. In Proceedings of the 35th International Conference on Machine Learning (ICML), 2018 [pdf].

1. 8.Raman Arora, Amitabh Basu, Poorya Mianjy, Anirbit Mukherjee. Understanding Deep Neural Networks with Rectified Linear Units. In Proceedings of the Sixth International Conference on Learning Representations (ICLR), 2018 [pdf].

1. 9.Raman Arora, Teodor Marinov and Poorya Mianjy. Stochastic approximation for canonical correlation analysis. Advances in Neural Information Processing Systems (NIPS) 2017 [pdf].

1. 10.Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Mingyi Hong. On Faster Convergence of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization. Journal of Machine Learning Research (JMLR), 2017 [pdf].

1. 11.Adrian Benton, Huda Khayrallah, Biman Gujral, Drew Reisinger, Sheng Zhang, Raman Arora. Deep Generalized Canonical Correlation Analysis. arXiv:1702.02519, 2017 [pdf].

1. 12.Xingguo Li, Zhaoran Wang, Junwei Lu, Raman Arora, Jarvis Haupt, Han Liu, Tuo Zhao. Symmetry, Saddle Points, and Global Geometry of Nonconvex Matrix Factorization. arXiv:1612.09296, 2017 [pdf].

1. 13.Xingguo Li, Raman Arora, Han Liu, Jarvis Haupt, Tuo Zhao. Nonconvex Sparse Learning via Stochastic Optimization with Progressive Variance Reduction. arXiv:1605.02711, 2016 [pdf].

1. 14.Peter Schulam and Raman Arora. Disease Trajectory Maps. Advances in Neural Information Processing Systems (NIPS) 2016, [pdf].

1. 15.Xingguo Li, Jarvis Haupt, Raman Arora, Han Liu, Mingyi Hong and Tuo Zhao. A first order free lunch for SQRT-Lasso. arXiv:1605.07950, 2016 [pdf]

1. 16.Raman Arora, Poorya Mianjy and Teodor Marinov. Stochastic optimization for multiview learning using partial least squares. In Proceedings of the 32nd International Conference on Machine Learning (ICML), 2016 [pdf].

1. 17.Xingguo Li, Tuo Zhao, Raman Arora, Han Liu and Jarvis Haupt. Stochastic variance reduced optimization for nonconvex sparse learning. In Proceedings of the 32nd International Conference on Machine Learning (ICML), 2016 [pdf] [supp].

1. 18.Adrian Benton, Raman Arora and Mark Dredze. Learning Multiview Embeddings of Twitter Users. In Proceedings of the Association for Computational Linguistics (ACL), 2016 [pdf].

1. 19.Mo Yu, Mark Dredze, Raman Arora and Matthew R. Gormley. Embedding lexical features via low-rank tensors. In Proceedings of the North American Chapter of the Association for Computational Linguistics (NAACL), 2016 [pdf].

1. 20.Weiran Wang, Raman Arora, Karen Livescu and Jeff Bilmes. On Deep Multi-View Representation Learning: Objectives and Optimization. arXiv, 2016 [pdf].

1. 21.Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Mingyi Hong. An improved convergence analysis of cyclic block coordinate descent-type methods for strongly convex minimization. In Proceedings of the 19th International conference on Artificial Intelligence and Statistics (AISTATS), 2016 [pdf] [supp].

1. 22.Weiran Wang, Raman Arora, Karen Livescu and Nathan Srebro. Stochastic optimization for deep CCA via nonlinear orthogonal iterations. In Proceedings of the 53rd Annual Allerton Conference on Communication, Control and Computing (ALLERTON), 2015 [pdf].

1. 23.Weiran Wang, Raman Arora, Karen Livescu and Jeff Bilmes. On Deep Multi-View Representation Learning. In Proceedings of the 32nd International Conference on Machine Learning (ICML), 2015 [pdf].

1. 24.Pushpendre Rastogi, Benjamin Van Durme and Raman Arora. Multiview LSA: Representation Learning via Generalized CCA. In Proceedings of the North American Chapter of the Association for Computational Linguistics (NAACL), 2015 [pdf].

1. 25.Weiran Wang, Raman Arora, Karen Livescu and Jeff Bilmes. Unsupervised learning of acoustic features via deep canonical correlation analysis. In Proceedings of the 39th International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2015 [pdf].

1. 26.Tuo Zhao, Mo Yu, Yiming Wang, Raman Arora, Han Liu. Accelerated mini-batch randomized block coordinate descent method. Advances in Neural Information Processing Systems (NIPS) 2014 [pdf].

1. 27.Weiran Wang, Raman Arora and Karen Livescu. Reconstruction of articulatory measurements with smoothed low-rank matrix completion. Spoken Language Technology (SLT) Workshop, 2014 [pdf].

1. 28.John Goes, Teng Zhang, Raman Arora and Gilad Lerman. Robust Stochastic Principal Component Analysis, In Proceedings of the 17th International conference on Artificial Intelligence and Statistics (AISTATS), 2014 [pdf].

1. 29.Raman Arora and Karen Livescu. Multi-view learning with supervision for transformed bottleneck features, In Proceedings of the 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014 [pdf].

1. 30.Raman Arora, Andy Cotter and Nati Srebro. Stochastic Optimization of PCA with Capped MSG. Advances in Neural Information Processing Systems (NIPS), 2013 (arXiv:1307.1674, Jul 2013) [pdf].

1. 31.Galen Andrew, Raman Arora, Jeff Bilmes and Karen Livescu. Deep Canonical Correlation Analysis. In Proceedings of the 30th International Conference on Machine Learning (ICML), 2013 [pdf].

1. 32.Raman Arora, Maya R. Gupta, Amol Kapila and Maryam Fazel. Similarity-based clustering by Left-Stochastic Matrix Factorization. Journal of Machine Learning Research (JMLR) 14.1, 2013: 1715-1746 [pdf].

1. 33.Raman Arora and Marina Meila. Consensus ranking with signed permutations. In Proceedings of the 16th International conference on Artificial Intelligence and Statistics (AISTATS), 2013 [pdf].

1. 34.Raman Arora and Karen Livescu. Multi-view CCA-based acoustic features for phonetic recognition across speakers and domains. In Proceedings of the 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2013 [pdf].

1. 35.Raman Arora, Ofer Dekel and Ambuj Tewari. Deterministic MDPs with adversarial rewards and bandit feedback. In Proceedings of the 28th Annual Conference on Uncertainty in Artificial Intelligence (UAI), 2012 [pdf].

1. 36.Raman Arora, Ofer Dekel and Ambuj Tewari. Online bandit learning against an adaptive adversary: from regret to policy regret. In Proceedings of the 29th International Conference on Machine Learning (ICML), 2012 [pdf].

1. 37.Raman Arora, Andy Cotter, Karen Livescu and Nati Srebro. Stochastic Optimization for PCA and PLS. In Proceedings of the 50th Annual Allerton Conference on Communication, Control and Computing (ALLERTON), 2012 [pdf].

1. 38.Raman Arora and Karen Livescu. Kernel CCA for multi-view acoustic feature learning using articulatory measurements. In Proceedings of the Machine Learning Symposium on Language and Speech Processing (MLSLP), 2012 [pdf].

1. 39.Eric K. Garcia, Raman Arora and Maya R. Gupta. Lattice regression for fast function evaluation with application to super-resolution and visual homing. In IEEE Transactions on Image Processing (IEEE TIP), 2012 [pdf].

1. 40.Sujeeth Bharadwaj, Raman Arora, Karen Livescu and Mark Hasegawa-Johnson. Multi-view acoustic feature learning using articulatory measurements. In International Workshop on Statistical Machine Learning for Speech Processing (IWSML), Apr 2012 [pdf].

1. 41.Raman Arora, Maya R. Gupta, Amol Kapila and Maryam Fazel. Clustering by Left-Stochastic Matrix Factorization. In Proceedings of the 28th International Conference on Machine Learning (ICML), 2011 [pdf].

1. 42.Raman Arora and Charles R. Dyer. Projective joint invariants for matching curves in camera networks. In Distributed Video Sensor Networks (DVSN), edited by B. Bhanu, C. V. Ravishankar, A. K. Roy-Chowdhury, H. Aghajan, D. Terzopoulos, Springer, 1st Edition, 2011, ISBN: 978-0-85729-126-4 [pdf].

1. 43.Raman Arora and William A. Sethares. An efficient and stable algorithm for learning rotations. In International conference on Pattern Recognition (ICPR), Istanbul, Turkey, Aug 2010 [pdf].

1. 44.Raman Arora and Harish Parthasarathy. Optimal estimation and detection in homogeneous spaces. In IEEE Transactions on Signal Processing (IEEE TSP), Volume 58, Issue 5, May 2010, Pages: 2623-2635 [pdf].

1. 45.Raman Arora, William A. Sethares and James Bucklew. Latent periodicities in genome sequences. In IEEE Journal of Selected Topics in Signal Processing (IEEE JSTSP): Genomic and Proteomic Sig. Proc., Vol 2, Issue 3, Jun 2008, Pages: 332-342 [pdf].

1. 46.Raman Arora and William A. Sethares. Adaptive wavetable oscillators. In IEEE Transactions on Signal Processing (IEEE TSP), Volume 55, Issue 9, 4382-4392, Sep 2007 [pdf].

Selected papers (reverse chronological order)