Nived Rajaraman

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 27

Top Topics

Correlation Clustering

Imitation Learning

Top Venues

Trans. Mach. Learn. Res.

Publications

Prafulla Chandra, Andrew Thangaraj, Nived Rajaraman
How good is Good-Turing for Markov samples? Trans. Mach. Learn. Res. 2024 (2024)
Nived Rajaraman, Marco Bondaschi, Kannan Ramchandran, Michael Gastpar, Ashok Vardhan Makkuva
Transformers on Markov Data: Constant Depth Suffices. CoRR (2024)
Nived Rajaraman, Jiantao Jiao, Kannan Ramchandran
Toward a Theory of Tokenization in LLMs. CoRR (2024)
Nived Rajaraman, Devvrit, Aryan Mokhtari, Kannan Ramchandran
Greedy Pruning with Group Lasso Provably Generalizes for Matrix Sensing. NeurIPS (2023)
Nived Rajaraman, Yanjun Han, Jiantao Jiao, Kannan Ramchandran
Beyond UCB: Statistical Complexity and Optimal Algorithms for Non-linear Ridge Bandits. CoRR (2023)
Dong Yin, Sridhar Thiagarajan, Nevena Lazic, Nived Rajaraman, Botao Hao, Csaba Szepesvári
Sample Efficient Deep Reinforcement Learning via Local Planning. CoRR (2023)
Nived Rajaraman, Devvrit, Aryan Mokhtari, Kannan Ramchandran
Greedy Pruning with Group Lasso Provably Generalizes for Matrix Sensing and Neural Networks with Quadratic Activations. CoRR (2023)
Amirali Aghazadeh, Nived Rajaraman, Tony Tu, Kannan Ramchandran
Spectral Regularization Allows Data-frugal Learning over Combinatorial Spaces. Trans. Mach. Learn. Res. 2023 (2023)
Prafulla Chandra, Andrew Thangaraj, Nived Rajaraman
Missing Mass Estimation from Sticky Channels. ISIT (2022)
Amirali Aghazadeh, Nived Rajaraman, Tony Tu, Kannan Ramchandran
Spectral Regularization Allows Data-frugal Learning over Combinatorial Spaces. CoRR (2022)
Gokul Swamy, Nived Rajaraman, Matthew Peng, Sanjiban Choudhury, J. Andrew Bagnell, Steven Wu, Jiantao Jiao, Kannan Ramchandran
Minimax Optimal Online Imitation Learning via Replay Estimation. NeurIPS (2022)
Nived Rajaraman, Fnu Devvrit, Pranjal Awasthi
Semi-supervised Active Linear Regression. NeurIPS (2022)
Gokul Swamy, Nived Rajaraman, Matthew Peng, Sanjiban Choudhury, J. Andrew Bagnell, Zhiwei Steven Wu, Jiantao Jiao, Kannan Ramchandran
Minimax Optimal Online Imitation Learning via Replay Estimation. CoRR (2022)
Nived Rajaraman, Yanjun Han, Lin F. Yang, Kannan Ramchandran, Jiantao Jiao
Provably Breaking the Quadratic Error Compounding Barrier in Imitation Learning, Optimally. CoRR (2021)
Fnu Devvrit, Nived Rajaraman, Pranjal Awasthi
Semi-supervised Active Regression. CoRR (2021)
Swanand Kadhe, Nived Rajaraman, Kannan Ramchandran
FastShare: Scalable Secret Sharing by Leveraging Locality. ISIT (2021)
Nived Rajaraman, Rahul Vaze, Goonwanth Reddy
Not Just Age but Age and Quality of Information. IEEE J. Sel. Areas Commun. 39 (5) (2021)
Nived Rajaraman, Yanjun Han, Lin Yang, Jingbo Liu, Jiantao Jiao, Kannan Ramchandran
On the Value of Interaction and Function Approximation in Imitation Learning. NeurIPS (2021)
Prafulla Chandra, Andrew Thangaraj, Nived Rajaraman
Missing Mass of Rank-2 Markov Chains. CoRR (2021)
Swanand Kadhe, Nived Rajaraman, Onur Ozan Koyluoglu, Kannan Ramchandran
FastSecAgg: Scalable Secure Aggregation for Privacy-Preserving Federated Learning. CoRR (2020)
Nived Rajaraman, Lin F. Yang, Jiantao Jiao, Kannan Ramchandran
Toward the Fundamental Limits of Imitation Learning. NeurIPS (2020)
Prafulla Chandra, Andrew Thangaraj, Nived Rajaraman
Missing Mass of Markov Chains. ISIT (2020)
Nived Rajaraman, Lin F. Yang, Jiantao Jiao, Kannan Ramchandran
Toward the Fundamental Limits of Imitation Learning. CoRR (2020)
Nived Rajaraman, Prafulla Chandra, Andrew Thangaraj, Ananda Theertha Suresh
Convergence of Chao Unseen Species Estimator. ISIT (2019)
Devvrit, Ravishankar Krishnaswamy, Nived Rajaraman
Robust Correlation Clustering. APPROX-RANDOM (2019)
Nived Rajaraman, Rahul Vaze
Submodular Maximization Under A Matroid Constraint: Asking more from an old friend, the Greedy Algorithm. CoRR (2018)
Nived Rajaraman, Rahul Vaze, Goonwanth Reddy
Not Just Age but Age and Quality of Information. CoRR (2018)