Equilibria of Adaptive Wavetable Oscillators with Applications to Beat Tracking. - William A. Sethares; Raman Arora (ICASSP (4), 2007)

Adaptive Wavetable Oscillators. - Raman Arora; William A. Sethares (IEEE Trans. Signal Process., 2007)

Localizing time-varying periodicities in symbolic sequences. - Raman Arora; William A. Sethares; James A. Bucklew (ICASSP, 2008)

Spherical Wiener filter. - Raman Arora; Harish Parthasarathy (ICIP, 2008)

Navigation using a spherical camera. - Raman Arora; Harish Parthasarathy (ICPR, 2008)

Latent Periodicities in Genome Sequences. - Raman Arora; William A. Sethares; James A. Bucklew (IEEE J. Sel. Top. Signal Process., 2008)

Reconstructing latent periods in genome sequences with insertions and deletions. - Raman Arora; Colin N. Dewey; William A. Sethares (GENSiPS, 2009)

Estimating correspondence between multiple cameras using joint invariants. - Raman Arora; Yu Hen Hu; Charles R. Dyer (ICASSP, 2009)

On Learning Rotations. - Raman Arora (NIPS, 2009)

Distributed curve matching in camera networks using projective joint invariant signatures. - Raman Arora; Charles R. Dyer; Yu Hen Hu; Nigel Boston (ICDSC, 2010)

An Efficient and Stable Algorithm for Learning Rotations. - Raman Arora; William A. Sethares (ICPR, 2010)

Optimal estimation and detection in homogeneous spaces. - Raman Arora; Harish Parthasarathy (IEEE Trans. Signal Process., 2010)

Minimizing bearing bias in tracking by de-coupled rotation and translation estimates. - Raman Arora; Maya R. Gupta (FUSION, 2011)

Clustering by Left-Stochastic Matrix Factorization. - Raman Arora; Maya R. Gupta; Amol Kapila; Maryam Fazel (ICML, 2011)

Stochastic optimization for PCA and PLS. - Raman Arora; Andrew Cotter; Karen Livescu; Nathan Srebro (Allerton Conference, 2012)

Online Bandit Learning against an Adaptive Adversary: from Regret to Policy Regret. - Ofer Dekel; Ambuj Tewari; Raman Arora (ICML, 2012)

Kernel CCA for multi-view learning of acoustic features using articulatory measurements. - Raman Arora; Karen Livescu (MLSLP, 2012)

Deterministic MDPs with Adversarial Rewards and Bandit Feedback. - Raman Arora; Ofer Dekel; Ambuj Tewari (UAI, 2012)

Optimized Regression for Efficient Function Evaluation. - Eric K. Garcia; Raman Arora; Maya R. Gupta (IEEE Trans. Image Process., 2012)

Consensus Ranking with Signed Permutations. - Raman Arora; Marina Meila (AISTATS, 2013)

Multi-view CCA-based acoustic features for phonetic recognition across speakers and domains. - Raman Arora; Karen Livescu (ICASSP, 2013)

Deep Canonical Correlation Analysis. - Galen Andrew; Raman Arora; Jeff A. Bilmes; Karen Livescu (ICML (3), 2013)

Stochastic Optimization of PCA with Capped MSG. - Raman Arora; Andrew Cotter; Nati Srebro (NIPS, 2013)

Similarity-based clustering by left-stochastic matrix factorization. - Raman Arora; Maya R. Gupta; Amol Kapila; Maryam Fazel (J. Mach. Learn. Res., 2013)

Robust Stochastic Principal Component Analysis. - John Goes; Teng Zhang 002; Raman Arora; Gilad Lerman (AISTATS, 2014)

Multi-view learning with supervision for transformed bottleneck features. - Raman Arora; Karen Livescu (ICASSP, 2014)

Accelerated Mini-batch Randomized Block Coordinate Descent Method. - Tuo Zhao; Mo Yu; Yiming Wang; Raman Arora; Han Liu 001 (NIPS, 2014)

Reconstruction of articulatory measurements with smoothed low-rank matrix completion. - Weiran Wang; Raman Arora; Karen Livescu (SLT, 2014)

Stochastic optimization for deep CCA via nonlinear orthogonal iterations. - Weiran Wang; Raman Arora; Karen Livescu; Nathan Srebro (Allerton, 2015)

Unsupervised learning of acoustic features via deep canonical correlation analysis. - Weiran Wang; Raman Arora; Karen Livescu; Jeff A. Bilmes (ICASSP, 2015)

On Deep Multi-View Representation Learning. - Weiran Wang; Raman Arora; Karen Livescu; Jeff A. Bilmes (ICML, 2015)

Multiview LSA: Representation Learning via Generalized CCA. - Pushpendre Rastogi; Benjamin Van Durme; Raman Arora (HLT-NAACL, 2015)

Learning Multiview Embeddings of Twitter Users. - Adrian Benton; Raman Arora; Mark Dredze (ACL (2), 2016)

An Improved Convergence Analysis of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization. - Xingguo Li; Tuo Zhao; Raman Arora; Han Liu 001; Mingyi Hong 001 (AISTATS, 2016)

Stochastic Optimization for Multiview Representation Learning using Partial Least Squares. - Raman Arora; Poorya Mianjy; Teodor V. Marinov (ICML, 2016)

Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning. - Xingguo Li; Tuo Zhao; Raman Arora; Han Liu 001; Jarvis D. Haupt (ICML, 2016)

Embedding Lexical Features via Low-Rank Tensors. - Mo Yu; Mark Dredze; Raman Arora; Matthew R. Gormley (HLT-NAACL, 2016)

Disease Trajectory Maps. - Peter Schulam; Raman Arora (NIPS, 2016)

A First Order Free Lunch for SQRT-Lasso. - Xingguo Li; Jarvis D. Haupt; Raman Arora; Han Liu 001; Mingyi Hong 001; Tuo Zhao (CoRR, 2016)

Symmetry, Saddle Points, and Global Geometry of Nonconvex Matrix Factorization. - Xingguo Li; Zhaoran Wang 001; Junwei Lu; Raman Arora; Jarvis D. Haupt; Han Liu 001; Tuo Zhao (CoRR, 2016)

On Deep Multi-View Representation Learning: Objectives and Optimization. - Weiran Wang; Raman Arora; Karen Livescu; Jeff A. Bilmes (CoRR, 2016)

On the impact of non-modal phonation on phonological features. - Milos Cernak; Elmar Nöth; Frank Rudzicz; Heidi Christensen; Juan Rafael Orozco-Arroyave; Raman Arora; Tobias Bocklet; Hamidreza Chinaei; Julius Hannink; Phani Sankar Nidadavolu; Juan Camilo Vásquez-Correa; Maria Yancheva; et al. (ICASSP, 2017)

Multi-view representation learning via gcca for multimodal analysis of Parkinson's disease. - Juan Camilo Vásquez-Correa; Juan Rafael Orozco-Arroyave; Raman Arora; Elmar Nöth; Najim Dehak; Heidi Christensen; Frank Rudzicz; Tobias Bocklet; Milos Cernak; Hamid R. Chinaei; Julius Hannink; Phani Sankar Nidadavolu; et al. (ICASSP, 2017)

A Speaker Adaptive DNN Training Approach for Speaker-Independent Acoustic Inversion. - Leonardo Badino; Luca Franceschi 001; Raman Arora; Michele Donini; Massimiliano Pontil (INTERSPEECH, 2017)

Stochastic Approximation for Canonical Correlation Analysis. - Raman Arora; Teodor Vanislavov Marinov; Poorya Mianjy; Nati Srebro (NIPS, 2017)

Stochastic Approximation for Canonical Correlation Analysis. - Raman Arora; Teodor V. Marinov; Poorya Mianjy (CoRR, 2017)

Learning to Imagine Manipulation Goals for Robot Task Planning. - Chris Paxton 001; Kapil D. Katyal; Christian Rupprecht 001; Raman Arora; Gregory D. Hager (CoRR, 2017)

Understanding Deep Neural Networks with Rectified Linear Units. - Raman Arora; Amitabh Basu; Poorya Mianjy; Anirbit Mukherjee (Electron. Colloquium Comput. Complex., 2017)

On Faster Convergence of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization. - Xingguo Li; Tuo Zhao; Raman Arora; Han Liu 001; Mingyi Hong 001 (J. Mach. Learn. Res., 2017)

Streaming Principal Component Analysis in Noisy Settings. - Teodor Vanislavov Marinov; Poorya Mianjy; Raman Arora (ICML, 2018)

Stochastic PCA with 𝓁2 and 𝓁1 Regularization. - Poorya Mianjy; Raman Arora (ICML, 2018)

On the Implicit Bias of Dropout. - Poorya Mianjy; Raman Arora; René Vidal (ICML, 2018)

Differentially Private Robust Low-Rank Approximation. - Raman Arora; Vladimir Braverman; Jalaj Upadhyay (NeurIPS, 2018)

Policy Regret in Repeated Games. - Raman Arora; Michael Dinitz; Teodor Vanislavov Marinov; Mehryar Mohri (NeurIPS, 2018)

Streaming Kernel PCA with tilde{O}( sqrt{n}) Random Features. - Enayat Ullah; Poorya Mianjy; Teodor Vanislavov Marinov; Raman Arora (NeurIPS, 2018)

The Physical Systems Behind Optimization Algorithms. - Lin F. Yang; Raman Arora; Vladimir Braverman; Tuo Zhao (NeurIPS, 2018)

Streaming Kernel PCA with Õ(√n) Random Features. - Enayat Ullah; Poorya Mianjy; Teodor V. Marinov; Raman Arora (CoRR, 2018)

NeuroSpeech: An open-source software for Parkinson's speech analysis. - Juan Rafael Orozco-Arroyave; Juan Camilo Vásquez-Correa; Jesús Francisco Vargas-Bonilla; Raman Arora; Najim Dehak; Phani S. Nidadavolu; Heidi Christensen; Frank Rudzicz; Maria Yancheva; Hamid R. Chinaei; Alyssa Vann; Nikolai Vogler; et al. (Digit. Signal Process., 2018)

NeuroSpeech. - Juan Rafael Orozco-Arroyave; Juan Camilo Vásquez-Correa; Jesús Francisco Vargas-Bonilla; Raman Arora; Najim Dehak; Phani S. Nidadavolu; Heidi Christensen; Frank Rudzicz; Maria Yancheva; Hamid R. Chinaei; Alyssa Vann; Nikolai Vogler; et al. (SoftwareX, 2018)

Learning from Multiview Correlations in Open-domain Videos. - Nils Holzenberger; Shruti Palaskar; Pranava Madhyastha; Florian Metze; Raman Arora (ICASSP, 2019)

On Dropout and Nuclear Norm Regularization. - Poorya Mianjy; Raman Arora (ICML, 2019)

Visual Robot Task Planning. - Chris Paxton 001; Yotam Barnoy; Kapil D. Katyal; Raman Arora; Gregory D. Hager (ICRA, 2019)

Efficient Convex Relaxations for Streaming PCA. - Raman Arora; Teodor Vanislavov Marinov (NeurIPS, 2019)

Bandits with Feedback Graphs and Switching Costs. - Raman Arora; Teodor Vanislavov Marinov; Mehryar Mohri (NeurIPS, 2019)

On Differentially Private Graph Sparsification and Applications. - Raman Arora; Jalaj Upadhyay (NeurIPS, 2019)

Communication-efficient Distributed SGD with Sketching. - Nikita Ivkin; Daniel Rothchild; Enayat Ullah; Vladimir Braverman; Ion Stoica; Raman Arora (NeurIPS, 2019)

Deep Generalized Canonical Correlation Analysis. - Adrian Benton; Huda Khayrallah; Biman Gujral; Dee Ann Reisinger; Sheng Zhang 012; Raman Arora (RepL4NLP@ACL, 2019)

On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don't Worry About its Nonsmooth Loss Function. - Xingguo Li; Haoming Jiang; Jarvis D. Haupt; Raman Arora; Han Liu 001; Mingyi Hong 001; Tuo Zhao (UAI, 2019)

Multiview Representation Learning for a Union of Subspaces. - Nils Holzenberger; Raman Arora (CoRR, 2019)

Symmetry, Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization. - Xingguo Li; Junwei Lu; Raman Arora; Jarvis D. Haupt; Han Liu 001; Zhaoran Wang 001; Tuo Zhao (IEEE Trans. Inf. Theory, 2019)

FetchSGD: Communication-Efficient Federated Learning with Sketching. - Daniel Rothchild; Ashwinee Panda; Enayat Ullah; Nikita Ivkin; Ion Stoica; Vladimir Braverman; Joseph Gonzalez 001; Raman Arora (ICML, 2020)

On Convergence and Generalization of Dropout Training. - Poorya Mianjy; Raman Arora (NeurIPS, 2020)

Adversarial Robustness of Supervised Sparse Coding. - Jeremias Sulam; Ramchandran Muthukumar; Raman Arora (NeurIPS, 2020)

Is Network the Bottleneck of Distributed Training? - Zhen Zhang 063; Chaokun Chang; Haibin Lin; Yida Wang 003; Raman Arora; Xin Jin 008 (NetAI@SIGCOMM, 2020)

Private Stochastic Convex Optimization: Efficient Algorithms for Non-smooth Objectives. - Raman Arora; Teodor V. Marinov; Enayat Ullah (CoRR, 2020)

Grounded Sequence to Sequence Transduction. - Lucia Specia; Loïc Barrault; Ozan Caglayan; Amanda Cardoso Duarte; Desmond Elliott; Spandana Gella; Nils Holzenberger; Chiraag Lala; Sun Jae Lee; Jindrich Libovický; Pranava Madhyastha; Florian Metze; et al. (IEEE J. Sel. Top. Signal Process., 2020)

Corralling Stochastic Bandit Algorithms. - Raman Arora; Teodor Vanislavov Marinov; Mehryar Mohri (AISTATS, 2021)

Differentially Private Analysis on Graph Streams. - Jalaj Upadhyay; Sarvagya Upadhyay; Raman Arora (AISTATS, 2021)

Machine Unlearning via Algorithmic Stability. - Enayat Ullah; Tung Mai; Anup Rao 002; Ryan A. Rossi; Raman Arora (COLT, 2021)

Dropout: Explicit Forms and Capacity Control. - Raman Arora; Peter L. Bartlett; Poorya Mianjy; Nathan Srebro (ICML, 2021)

Robust Learning for Data Poisoning Attacks. - Yunjuan Wang; Poorya Mianjy; Raman Arora (ICML, 2021)

Differentially Private Generalized Linear Models Revisited. - Raman Arora; Raef Bassily; Cristóbal Guzmán; Michael Menart; Enayat Ullah (NeurIPS, 2022)

Adversarial Robustness is at Odds with Lazy Training. - Yunjuan Wang; Enayat Ullah; Poorya Mianjy; Raman Arora (NeurIPS, 2022)

Multiuser Scheduling in Centralized Cognitive Radio Networks: A Multi-Armed Bandit Approach. - Amir Alipour-Fanid; Monireh Dabaghchian; Raman Arora; Kai Zeng 001 (IEEE Trans. Cogn. Commun. Netw., 2022)

A Risk-Sensitive Approach to Policy Optimization. - Jared Markowitz; Ryan W. Gardner; Ashley J. Llorens; Raman Arora; I-Jeng Wang (AAAI, 2023)

On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation. - Thanh Nguyen-Tang; Ming Yin; Sunil Gupta 001; Svetha Venkatesh; Raman Arora (AAAI, 2023)

VIPeR: Provably Efficient Algorithm for Offline RL with Neural Function Approximation. - Thanh Nguyen-Tang; Raman Arora (ICLR, 2023)

Faster Rates of Convergence to Stationary Points in Differentially Private Optimization. - Raman Arora; Raef Bassily; Tomás González; Cristóbal Guzmán; Michael Menart; Enayat Ullah (ICML, 2023)

From Adaptive Query Release to Machine Unlearning. - Enayat Ullah; Raman Arora (ICML, 2023)

Multi-Agent Learning with Heterogeneous Linear Contextual Bandits. - Anh Do; Thanh Nguyen-Tang; Raman Arora (NeurIPS, 2023)

Robustness Guarantees for Adversarially Trained Neural Networks. - Poorya Mianjy; Raman Arora (NeurIPS, 2023)

On Sample-Efficient Offline Reinforcement Learning: Data Diversity, Posterior Sampling and Beyond. - Thanh Nguyen-Tang; Raman Arora (NeurIPS, 2023)

Optimistic Rates for Multi-Task Representation Learning. - Austin Watkins; Enayat Ullah; Thanh Nguyen-Tang; Raman Arora (NeurIPS, 2023)

Provably Efficient Neural Offline Reinforcement Learning via Perturbed Rewards. - Thanh Nguyen-Tang; Raman Arora (CoRR, 2023)

Generalization bounds for Kernel Canonical Correlation Analysis. - Enayat Ullah; Raman Arora (Trans. Mach. Learn. Res., 2023)

Clustering using Approximate Nearest Neighbour Oracles. - Enayat Ullah; Harry Lang; Raman Arora; Vladimir Braverman (Trans. Mach. Learn. Res., 2023)

Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates. - Michael Menart; Enayat Ullah; Raman Arora; Raef Bassily; Cristóbal Guzmán (ALT, 2024)

On The Statistical Complexity of Offline Decision-Making. - Thanh Nguyen-Tang; Raman Arora (ICML, 2024)

Adversarially Robust Hypothesis Transfer Learning. - Yunjuan Wang; Raman Arora (ICML, 2024)

Benign Overfitting in Adversarial Training of Neural Networks. - Yunjuan Wang; Kaibo Zhang; Raman Arora (ICML, 2024)

Offline Multitask Representation Learning for Reinforcement Learning. - Haque Ishfaq; Thanh Nguyen-Tang; Songtao Feng; Raman Arora; Mengdi Wang; Ming Yin 003; Doina Precup (NeurIPS, 2024)

Learning in Markov Games with Adaptive Adversaries: Policy Regret, Fundamental Barriers, and Efficient Algorithms. - Thanh Nguyen-Tang; Raman Arora (NeurIPS, 2024)

Public-data Assisted Private Stochastic Optimization: Power and Limitations. - Enayat Ullah; Michael Menart; Raef Bassily; Cristóbal Guzmán; Raman Arora (NeurIPS, 2024)

On the Stability and Generalization of Meta-Learning. - Yunjuan Wang; Raman Arora (NeurIPS, 2024)

Adversarially Robust Multi-task Representation Learning. - Austin Watkins; Thanh Nguyen-Tang; Enayat Ullah; Raman Arora (NeurIPS, 2024)

Stability and Generalization of Adversarial Training for Shallow Neural Networks with Smooth Activation. - Kaibo Zhang; Yunjuan Wang; Raman Arora (NeurIPS, 2024)

DART: A Principled Approach to Adversarially Robust Unsupervised Domain Adaptation. - Yunjuan Wang; Hussein Hazimeh 001; Natalia Ponomareva 001; Alexey Kurakin; Ibrahim Hammoud; Raman Arora (SaTML, 2025)