Nived Rajaraman

40 papers A* 10B 4Journal 25Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Interactive Learning of Single-Index Models via Stochastic Gradient Descent. CoRR Nived Rajaraman, Yanjun Han
2026	J	`jnl`	Learning to Reason with Curriculum I: Provable Benefits of Autocurriculum. CoRR Nived Rajaraman, Audrey Huang, Miroslav Dudík, Robert E. Schapire, Dylan J. Foster, Akshay Krishnamurthy
2025	A*	`conf`	Computational Intractability of Strategizing against Online Learners. COLT Angelos Assos, Yuval Dagan, Nived Rajaraman
2025	J	`jnl`	Computational Intractability of Strategizing against Online Learners. CoRR Angelos Assos, Yuval Dagan, Nived Rajaraman
2025	J	`jnl`	From Markov to Laplace: How Mamba In-Context Learns Markov Chains. CoRR Marco Bondaschi, Nived Rajaraman, Xiuying Wei, Kannan Ramchandran, Razvan Pascanu, Caglar Gulcehre, Michael Gastpar, Ashok Vardhan Makkuva
2025	J	`jnl`	SPECS: Faster Test-Time Scaling through Speculative Drafts. CoRR Mert Cemri, Nived Rajaraman, Rishabh Tiwari, Xiaoxuan Liu, Kurt Keutzer, Ion Stoica, Kannan Ramchandran, Ahmad Beirami, Ziteng Sun
2025	A*	`conf`	Scaling Test-Time Compute Without Verification or RL is Suboptimal. ICML Amrith Setlur, Nived Rajaraman, Sergey Levine, Aviral Kumar
2025	J	`jnl`	Scaling Test-Time Compute Without Verification or RL is Suboptimal. CoRR Amrith Setlur, Nived Rajaraman, Sergey Levine, Aviral Kumar
2025	A*	`conf`	The Space Complexity of Learning-Unlearning Algorithms (extended abstract). COLT Yeshwanth Cherapanamjeri, Sumegba Garg, Nived Rajaraman, Ayush Sekhari, Abhishek Shetty
2025	J	`jnl`	The Space Complexity of Learning-Unlearning Algorithms. CoRR Yeshwanth Cherapanamjeri, Sumegha Garg, Nived Rajaraman, Ayush Sekhari, Abhishek Shetty
2025	J	`jnl`	What One Cannot, Two Can: Two-Layer Transformers Provably Represent Induction Heads on Any-Order Markov Chains. CoRR Chanakya Ekbote, Marco Bondaschi, Nived Rajaraman, Jason D. Lee, Michael Gastpar, Ashok Vardhan Makkuva, Paul Pu Liang
2024	A*	`conf`	An Analysis of Tokenization: Transformers under Markov Data. NeurIPS Nived Rajaraman, Jiantao Jiao, Kannan Ramchandran
2024	J	`jnl`	How good is Good-Turing for Markov samples? Trans. Mach. Learn. Res. Prafulla Chandra, Andrew Thangaraj, Nived Rajaraman
2024	J	`jnl`	Toward a Theory of Tokenization in LLMs. CoRR Nived Rajaraman, Jiantao Jiao, Kannan Ramchandran
2024	J	`jnl`	Transformers on Markov Data: Constant Depth Suffices. CoRR Nived Rajaraman, Marco Bondaschi, Kannan Ramchandran, Michael Gastpar, Ashok Vardhan Makkuva
2024	A*	`conf`	Transformers on Markov data: Constant depth suffices. NeurIPS Nived Rajaraman, Marco Bondaschi, Ashok Vardhan Makkuva, Kannan Ramchandran, Michael Gastpar
2023	J	`jnl`	Beyond UCB: Statistical Complexity and Optimal Algorithms for Non-linear Ridge Bandits. CoRR Nived Rajaraman, Yanjun Han, Jiantao Jiao, Kannan Ramchandran
2023	J	`jnl`	Greedy Pruning with Group Lasso Provably Generalizes for Matrix Sensing and Neural Networks with Quadratic Activations. CoRR Nived Rajaraman, Devvrit, Aryan Mokhtari, Kannan Ramchandran
2023	A*	`conf`	Greedy Pruning with Group Lasso Provably Generalizes for Matrix Sensing. NeurIPS Nived Rajaraman, Devvrit, Aryan Mokhtari, Kannan Ramchandran
2023	J	`jnl`	Sample Efficient Deep Reinforcement Learning via Local Planning. CoRR Dong Yin, Sridhar Thiagarajan, Nevena Lazic, Nived Rajaraman, Botao Hao, Csaba Szepesvári
2023	J	`jnl`	Spectral Regularization Allows Data-frugal Learning over Combinatorial Spaces. Trans. Mach. Learn. Res. Amirali Aghazadeh, Nived Rajaraman, Tony Tu, Kannan Ramchandran
2022	A*	`conf`	Minimax Optimal Online Imitation Learning via Replay Estimation. NeurIPS Gokul Swamy, Nived Rajaraman, Matthew Peng, Sanjiban Choudhury, J. Andrew Bagnell, Steven Wu, Jiantao Jiao, Kannan Ramchandran
2022	J	`jnl`	Minimax Optimal Online Imitation Learning via Replay Estimation. CoRR Gokul Swamy, Nived Rajaraman, Matthew Peng, Sanjiban Choudhury, J. Andrew Bagnell, Zhiwei Steven Wu, Jiantao Jiao, Kannan Ramchandran
2022	B	`conf`	Missing Mass Estimation from Sticky Channels. ISIT Prafulla Chandra, Andrew Thangaraj, Nived Rajaraman
2022	A*	`conf`	Semi-supervised Active Linear Regression. NeurIPS Nived Rajaraman, Devvrit, Pranjal Awasthi
2022	J	`jnl`	Spectral Regularization Allows Data-frugal Learning over Combinatorial Spaces. CoRR Amirali Aghazadeh, Nived Rajaraman, Tony Tu, Kannan Ramchandran
2021	B	`conf`	FastShare: Scalable Secret Sharing by Leveraging Locality. ISIT Swanand Kadhe, Nived Rajaraman, Kannan Ramchandran
2021	J	`jnl`	Missing Mass of Rank-2 Markov Chains. CoRR Prafulla Chandra, Andrew Thangaraj, Nived Rajaraman
2021	J	`jnl`	Not Just Age but Age and Quality of Information. IEEE J. Sel. Areas Commun. Nived Rajaraman, Rahul Vaze, Goonwanth Reddy
2021	A*	`conf`	On the Value of Interaction and Function Approximation in Imitation Learning. NeurIPS Nived Rajaraman, Yanjun Han, Lin Yang, Jingbo Liu, Jiantao Jiao, Kannan Ramchandran
2021	J	`jnl`	Provably Breaking the Quadratic Error Compounding Barrier in Imitation Learning, Optimally. CoRR Nived Rajaraman, Yanjun Han, Lin F. Yang, Kannan Ramchandran, Jiantao Jiao
2021	J	`jnl`	Semi-supervised Active Regression. CoRR Devvrit, Nived Rajaraman, Pranjal Awasthi
2020	J	`jnl`	FastSecAgg: Scalable Secure Aggregation for Privacy-Preserving Federated Learning. CoRR Swanand Kadhe, Nived Rajaraman, Onur Ozan Koyluoglu, Kannan Ramchandran
2020	B	`conf`	Missing Mass of Markov Chains. ISIT Prafulla Chandra, Andrew Thangaraj, Nived Rajaraman
2020	A*	`conf`	Toward the Fundamental Limits of Imitation Learning. NeurIPS Nived Rajaraman, Lin F. Yang, Jiantao Jiao, Kannan Ramchandran
2020	J	`jnl`	Toward the Fundamental Limits of Imitation Learning. CoRR Nived Rajaraman, Lin F. Yang, Jiantao Jiao, Kannan Ramchandran
2019	B	`conf`	Convergence of Chao Unseen Species Estimator. ISIT Nived Rajaraman, Prafulla Chandra, Andrew Thangaraj, Ananda Theertha Suresh
2019	—	`conf`	Robust Correlation Clustering. APPROX-RANDOM Devvrit, Ravishankar Krishnaswamy, Nived Rajaraman
2018	J	`jnl`	Not Just Age but Age and Quality of Information. CoRR Nived Rajaraman, Rahul Vaze, Goonwanth Reddy
2018	J	`jnl`	Submodular Maximization Under A Matroid Constraint: Asking more from an old friend, the Greedy Algorithm. CoRR Nived Rajaraman, Rahul Vaze