Raman Arora

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 104

Top Venues

CoRR

NeurIPS

ICML

ICASSP

Publications

Michael Menart, Enayat Ullah, Raman Arora, Raef Bassily, Cristóbal Guzmán
Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates. ALT (2024)
Enayat Ullah, Michael Menart, Raef Bassily, Cristóbal Guzmán, Raman Arora
Public-data Assisted Private Stochastic Optimization: Power and Limitations. CoRR (2024)
Yunjuan Wang, Hussein Hazimeh, Natalia Ponomareva, Alexey Kurakin, Ibrahim Hammoud, Raman Arora
DART: A Principled Approach to Adversarially Robust Unsupervised Domain Adaptation. CoRR (2024)
Thanh Nguyen-Tang, Raman Arora
On Sample-Efficient Offline Reinforcement Learning: Data Diversity, Posterior Sampling, and Beyond. CoRR (2024)
Haque Ishfaq, Thanh Nguyen-Tang, Songtao Feng, Raman Arora, Mengdi Wang, Ming Yin, Doina Precup
Offline Multitask Representation Learning for Reinforcement Learning. CoRR (2024)
Anh Do, Thanh Nguyen-Tang, Raman Arora
Multi-Agent Learning with Heterogeneous Linear Contextual Bandits. NeurIPS (2023)
Enayat Ullah, Raman Arora
Generalization bounds for Kernel Canonical Correlation Analysis. Trans. Mach. Learn. Res. 2023 (2023)
Enayat Ullah, Harry Lang, Raman Arora, Vladimir Braverman
Clustering using Approximate Nearest Neighbour Oracles. Trans. Mach. Learn. Res. 2023 (2023)
Thanh Nguyen-Tang, Raman Arora
VIPeR: Provably Efficient Algorithm for Offline RL with Neural Function Approximation. ICLR (2023)
Raman Arora, Raef Bassily, Tomás González, Cristóbal Guzmán, Michael Menart, Enayat Ullah
Faster Rates of Convergence to Stationary Points in Differentially Private Optimization. ICML (2023)
Thanh Nguyen-Tang, Raman Arora
On Sample-Efficient Offline Reinforcement Learning: Data Diversity, Posterior Sampling and Beyond. NeurIPS (2023)
Michael Menart, Enayat Ullah, Raman Arora, Raef Bassily, Cristóbal Guzmán
Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates. CoRR (2023)
Jared Markowitz, Ryan W. Gardner, Ashley J. Llorens, Raman Arora, I-Jeng Wang
A Risk-Sensitive Approach to Policy Optimization. AAAI (2023)
Thanh Nguyen-Tang, Raman Arora
Provably Efficient Neural Offline Reinforcement Learning via Perturbed Rewards. CoRR (2023)
Poorya Mianjy, Raman Arora
Robustness Guarantees for Adversarially Trained Neural Networks. NeurIPS (2023)
Thanh Nguyen-Tang, Ming Yin, Sunil Gupta, Svetha Venkatesh, Raman Arora
On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation. AAAI (2023)
Austin Watkins, Enayat Ullah, Thanh Nguyen-Tang, Raman Arora
Optimistic Rates for Multi-Task Representation Learning. NeurIPS (2023)
Enayat Ullah, Raman Arora
From Adaptive Query Release to Machine Unlearning. ICML (2023)
Enayat Ullah, Raman Arora
From Adaptive Query Release to Machine Unlearning. CoRR (2023)
Yunjuan Wang, Enayat Ullah, Poorya Mianjy, Raman Arora
Adversarial Robustness is at Odds with Lazy Training. NeurIPS (2022)
Raman Arora, Raef Bassily, Cristóbal Guzmán, Michael Menart, Enayat Ullah
Differentially Private Generalized Linear Models Revisited. CoRR (2022)
Thanh Nguyen-Tang, Ming Yin, Sunil Gupta, Svetha Venkatesh, Raman Arora
On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation. CoRR (2022)
Jared Markowitz, Ryan W. Gardner, Ashley J. Llorens, Raman Arora, I-Jeng Wang
A Risk-Sensitive Approach to Policy Optimization. CoRR (2022)
Raman Arora, Raef Bassily, Cristóbal Guzmán, Michael Menart, Enayat Ullah
Differentially Private Generalized Linear Models Revisited. NeurIPS (2022)
Raman Arora, Raef Bassily, Tomás González, Cristóbal Guzmán, Michael Menart, Enayat Ullah
Faster Rates of Convergence to Stationary Points in Differentially Private Optimization. CoRR (2022)
Yunjuan Wang, Enayat Ullah, Poorya Mianjy, Raman Arora
Adversarial Robustness is at Odds with Lazy Training. CoRR (2022)
Amir Alipour-Fanid, Monireh Dabaghchian, Raman Arora, Kai Zeng
Multiuser Scheduling in Centralized Cognitive Radio Networks: A Multi-Armed Bandit Approach. IEEE Trans. Cogn. Commun. Netw. 8 (2) (2022)
Enayat Ullah, Tung Mai, Anup Rao, Ryan A. Rossi, Raman Arora
Machine Unlearning via Algorithmic Stability. CoRR (2021)
Enayat Ullah, Tung Mai, Anup Rao, Ryan A. Rossi, Raman Arora
Machine Unlearning via Algorithmic Stability. COLT (2021)
Jalaj Upadhyay, Sarvagya Upadhyay, Raman Arora
Differentially Private Analysis on Graph Streams. AISTATS (2021)
Raman Arora, Peter Bartlett, Poorya Mianjy, Nathan Srebro
Dropout: Explicit Forms and Capacity Control. ICML (2021)
Raman Arora, Teodor Vanislavov Marinov, Mehryar Mohri
Corralling Stochastic Bandit Algorithms. AISTATS (2021)
Yunjuan Wang, Poorya Mianjy, Raman Arora
Robust Learning for Data Poisoning Attacks. ICML (2021)
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, Karl Mulligan, Alissa Ostapenko, Shruti Palaskar, Ramon Sanabria, Josiah Wang, Raman Arora
Grounded Sequence to Sequence Transduction. IEEE J. Sel. Top. Signal Process. 14 (3) (2020)
Raman Arora, Teodor V. Marinov, Enayat Ullah
Private Stochastic Convex Optimization: Efficient Algorithms for Non-smooth Objectives. CoRR (2020)
Jeremias Sulam, Ramchandran Muthukumar, Raman Arora
Adversarial Robustness of Supervised Sparse Coding. CoRR (2020)
Jeremias Sulam, Ramchandran Muthukumar, Raman Arora
Adversarial Robustness of Supervised Sparse Coding. NeurIPS (2020)
Daniel Rothchild, Ashwinee Panda, Enayat Ullah, Nikita Ivkin, Ion Stoica, Vladimir Braverman, Joseph Gonzalez, Raman Arora
FetchSGD: Communication-Efficient Federated Learning with Sketching. ICML (2020)
Raman Arora, Teodor V. Marinov, Mehryar Mohri
Corralling Stochastic Bandit Algorithms. CoRR (2020)
Raman Arora, Peter Bartlett, Poorya Mianjy, Nathan Srebro
Dropout: Explicit Forms and Capacity Control. CoRR (2020)
Poorya Mianjy, Raman Arora
On Convergence and Generalization of Dropout Training. CoRR (2020)
Daniel Rothchild, Ashwinee Panda, Enayat Ullah, Nikita Ivkin, Ion Stoica, Vladimir Braverman, Joseph Gonzalez, Raman Arora
FetchSGD: Communication-Efficient Federated Learning with Sketching. CoRR (2020)
Zhen Zhang, Chaokun Chang, Haibin Lin, Yida Wang, Raman Arora, Xin Jin
Is Network the Bottleneck of Distributed Training? CoRR (2020)
Zhen Zhang, Chaokun Chang, Haibin Lin, Yida Wang, Raman Arora, Xin Jin
Is Network the Bottleneck of Distributed Training? NetAI@SIGCOMM (2020)
Poorya Mianjy, Raman Arora
On Convergence and Generalization of Dropout Training. NeurIPS (2020)
Chris Paxton, Yotam Barnoy, Kapil D. Katyal, Raman Arora, Gregory D. Hager
Visual Robot Task Planning. ICRA (2019)
Xingguo Li, Haoming Jiang, Jarvis D. Haupt, Raman Arora, Han Liu, Mingyi Hong, Tuo Zhao
On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don't Worry About its Nonsmooth Loss Function. UAI (2019)
Poorya Mianjy, Raman Arora
On Dropout and Nuclear Norm Regularization. CoRR (2019)
Nikita Ivkin, Daniel Rothchild, Enayat Ullah, Vladimir Braverman, Ion Stoica, Raman Arora
Communication-efficient distributed SGD with Sketching. CoRR (2019)
Adrian Benton, Huda Khayrallah, Biman Gujral, Dee Ann Reisinger, Sheng Zhang, Raman Arora
Deep Generalized Canonical Correlation Analysis. RepL4NLP@ACL (2019)
Raman Arora, Teodor V. Marinov, Mehryar Mohri
Bandits with Feedback Graphs and Switching Costs. CoRR (2019)
Nikita Ivkin, Daniel Rothchild, Enayat Ullah, Vladimir Braverman, Ion Stoica, Raman Arora
Communication-efficient Distributed SGD with Sketching. NeurIPS (2019)
Raman Arora, Teodor Vanislavov Marinov
Efficient Convex Relaxations for Streaming PCA. NeurIPS (2019)
Nils Holzenberger, Raman Arora
Multiview Representation Learning for a Union of Subspaces. CoRR (2019)
Raman Arora, Teodor Vanislavov Marinov, Mehryar Mohri
Bandits with Feedback Graphs and Switching Costs. NeurIPS (2019)
Xingguo Li, Junwei Lu, Raman Arora, Jarvis D. Haupt, Han Liu, Zhaoran Wang, Tuo Zhao
Symmetry, Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization. IEEE Trans. Inf. Theory 65 (6) (2019)
Nils Holzenberger, Shruti Palaskar, Pranava Madhyastha, Florian Metze, Raman Arora
Learning from Multiview Correlations in Open-domain Videos. ICASSP (2019)
Poorya Mianjy, Raman Arora
On Dropout and Nuclear Norm Regularization. ICML (2019)
Raman Arora, Jalaj Upadhyay
On Differentially Private Graph Sparsification and Applications. NeurIPS (2019)
Poorya Mianjy, Raman Arora, René Vidal
On the Implicit Bias of Dropout. CoRR (2018)
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, Tobias Bocklet, Milos Cernak, Julius Hannink, Elmar Nöth
NeuroSpeech: An open-source software for Parkinson's speech analysis. Digit. Signal Process. 77 (2018)
Raman Arora, Michael Dinitz, Teodor Vanislavov Marinov, Mehryar Mohri
Policy Regret in Repeated Games. NeurIPS (2018)
Enayat Ullah, Poorya Mianjy, Teodor V. Marinov, Raman Arora
Streaming Kernel PCA with Õ(√n) Random Features. CoRR (2018)
Teodor Vanislavov Marinov, Poorya Mianjy, Raman Arora
Streaming Principal Component Analysis in Noisy Settings. ICML (2018)
Xingguo Li, Jarvis D. Haupt, Junwei Lu, Zhaoran Wang, Raman Arora, Han Liu, Tuo Zhao
Symmetry. Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization. ITA (2018)
Lin F. Yang, Raman Arora, Vladimir Braverman, Tuo Zhao
The Physical Systems Behind Optimization Algorithms. NeurIPS (2018)
Raman Arora, Amitabh Basu, Poorya Mianjy, Anirbit Mukherjee
Understanding Deep Neural Networks with Rectified Linear Units. ICLR (Poster) (2018)
Chris Paxton, Yotam Barnoy, Kapil D. Katyal, Raman Arora, Gregory D. Hager
Visual Robot Task Planning. CoRR (2018)
Poorya Mianjy, Raman Arora, René Vidal
On the Implicit Bias of Dropout. ICML (2018)
Enayat Ullah, Poorya Mianjy, Teodor Vanislavov Marinov, Raman Arora
Streaming Kernel PCA with \tilde{O}(\sqrt{n}) Random Features. NeurIPS (2018)
Poorya Mianjy, Raman Arora
Regularization. ICML (2018)
Raman Arora, Michael Dinitz, Teodor V. Marinov, Mehryar Mohri
Policy Regret in Repeated Games. CoRR (2018)
Raman Arora, Vladimir Braverman, Jalaj Upadhyay
Differentially Private Robust Low-Rank Approximation. NeurIPS (2018)
Nils Holzenberger, Shruti Palaskar, Pranava Madhyastha, Florian Metze, Raman Arora
Learning from Multiview Correlations in Open-Domain Videos. CoRR (2018)
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, Tobias Bocklet, Milos Cernak, Julius Hannink, Elmar Nöth
NeuroSpeech. SoftwareX 8 (2018)
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, Maria Yancheva, Alyssa Vann, Nikolai Vogler
Multi-view representation learning via gcca for multimodal analysis of Parkinson's disease. ICASSP (2017)
Chris Paxton, Kapil D. Katyal, Christian Rupprecht, Raman Arora, Gregory D. Hager
Learning to Imagine Manipulation Goals for Robot Task Planning. CoRR (2017)
Raman Arora, Teodor Vanislavov Marinov, Poorya Mianjy, Nati Srebro
Stochastic Approximation for Canonical Correlation Analysis. NIPS (2017)
Raman Arora, Teodor V. Marinov, Poorya Mianjy
Stochastic Approximation for Canonical Correlation Analysis. CoRR (2017)
Adrian Benton, Huda Khayrallah, Biman Gujral, Dee Ann Reisinger, Sheng Zhang, Raman Arora
Deep Generalized Canonical Correlation Analysis. CoRR (2017)
Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Mingyi Hong
On Faster Convergence of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization. J. Mach. Learn. Res. 18 (2017)
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, Alyssa Vann, Nikolai Vogler
On the impact of non-modal phonation on phonological features. ICASSP (2017)
Leonardo Badino, Luca Franceschi, Raman Arora, Michele Donini, Massimiliano Pontil
A Speaker Adaptive DNN Training Approach for Speaker-Independent Acoustic Inversion. INTERSPEECH (2017)
Raman Arora, Amitabh Basu, Poorya Mianjy, Anirbit Mukherjee
Understanding Deep Neural Networks with Rectified Linear Units. Electron. Colloquium Comput. Complex. 24 (2017)
Xingguo Li, Zhaoran Wang, Junwei Lu, Raman Arora, Jarvis D. Haupt, Han Liu, Tuo Zhao
Symmetry, Saddle Points, and Global Geometry of Nonconvex Matrix Factorization. CoRR (2016)
Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Jarvis D. Haupt
Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning. CoRR (2016)
Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Jarvis D. Haupt
Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning. ICML (2016)
Adrian Benton, Raman Arora, Mark Dredze
Learning Multiview Embeddings of Twitter Users. ACL (2) (2016)
Weiran Wang, Raman Arora, Karen Livescu, Jeff A. Bilmes
On Deep Multi-View Representation Learning: Objectives and Optimization. CoRR (2016)
Raman Arora, Poorya Mianjy, Teodor V. Marinov
Stochastic Optimization for Multiview Representation Learning using Partial Least Squares. ICML (2016)
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. CoRR (2016)
Peter Schulam, Raman Arora
Disease Trajectory Maps. CoRR (2016)
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. AISTATS (2016)
Raman Arora, Amitabh Basu, Poorya Mianjy, Anirbit Mukherjee
Understanding Deep Neural Networks with Rectified Linear Units. CoRR (2016)
Xingguo Li, Jarvis D. Haupt, Raman Arora, Han Liu, Mingyi Hong, Tuo Zhao
A First Order Free Lunch for SQRT-Lasso. CoRR (2016)
Lin F. Yang, Raman Arora, Vladimir Braverman, Tuo Zhao
The Physical Systems Behind Optimization Algorithms. CoRR (2016)
Mo Yu, Mark Dredze, Raman Arora, Matthew R. Gormley
Embedding Lexical Features via Low-Rank Tensors. HLT-NAACL (2016)
Peter Schulam, Raman Arora
Disease Trajectory Maps. NIPS (2016)
Mo Yu, Mark Dredze, Raman Arora, Matthew R. Gormley
Embedding Lexical Features via Low-Rank Tensors. CoRR (2016)
Weiran Wang, Raman Arora, Karen Livescu, Jeff A. Bilmes
Unsupervised learning of acoustic features via deep canonical correlation analysis. ICASSP (2015)

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Publication Activity (10 Years)

Top Topics

Top Venues

Raman Arora