113 citations · 146 across the 25 of their papers we have counts for
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Greedy Pruning with Group Lasso Provably Generalizes for Matrix Sensing
Nived Rajaraman, Devvrit, Aryan Mokhtari +1
Pruning schemes have been widely used in practice to reduce the complexity of trained models with a massive number of parameters. In fact, several practical studies have shown that…
Statistical Complexity and Optimal Algorithms for Non-linear Ridge Bandits
Nived Rajaraman, Yanjun Han, Jiantao Jiao +1
We consider the sequential decision-making problem where the mean outcome is a non-linear function of the chosen action. Compared with the linear model, two curious phenomena arise…
Sample Efficient Deep Reinforcement Learning via Local Planning
Dong Yin, Sridhar Thiagarajan, Nevena Lazic +3
The focus of this work is sample-efficient deep reinforcement learning (RL) with a simulator. One useful property of simulators is that it is typically easy to reset the environmen…