Nived Rajaraman
11 papers · 2020–2026 · 3 venues · across top CS/AI venues
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Machine Learning
(9)
Optimization & Theory
(6)
Learning Types Β· Machine Learning
(4)
Artificial Intelligence
(3)
Deep Learning
(3)
Reinforcement Learning
(3)
Core AI
(3)
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(3)
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(1)
Natural Language Processing
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(1)
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reinforcement learning
(3)
imitation learning
(3)
active learning
(2)
online learning
(2)
markov process
(2)
behavior cloning
(2)
language modeling
(1)
in-context learning
(1)
sequence modeling
(1)
attention mechanism
(1)
linear function approximation
(1)
chain-of-thought reasoning
(1)
curriculum learning
(1)
policy learning
(1)
markov decision process
(1)
policy gradient
(1)
group lasso
(1)
vc dimension
(1)
statistical learning theory
(1)
semi-supervised learning
(1)
Papers
Learning to Reason with Curriculum I: Provable Benefits of Autocurriculum
COLT 2026
Computational Intractability of Strategizing against Online Learners
COLT 2025
Scaling Test-Time Compute Without Verification or RL is Suboptimal
ICML 2025
The Space Complexity of Learning-Unlearning Algorithms (extended abstract)
COLT 2025
An Analysis of Tokenization: Transformers under Markov Data
NeurIPS 2024
Transformers on Markov data: Constant depth suffices
NeurIPS 2024
Greedy Pruning with Group Lasso Provably Generalizes for Matrix Sensing
NeurIPS 2023
Minimax Optimal Online Imitation Learning via Replay Estimation
NeurIPS 2022
Semi-supervised Active Linear Regression
NeurIPS 2022
On the Value of Interaction and Function Approximation in Imitation Learning
NeurIPS 2021
Toward the Fundamental Limits of Imitation Learning
NeurIPS 2020