113 citations · 135 across the 7 of their papers we have counts for
9 papers
Spectral Regularization Allows Data-frugal Learning over Combinatorial Spaces
Amirali Aghazadeh, Nived Rajaraman, Tony Tu +1
Data-driven machine learning models are being increasingly employed in several important inference problems in biology, chemistry, and physics which require learning over combinato…
Missing Mass Estimation from Sticky Channels
Prafulla Chandra, Andrew Thangaraj, Nived Rajaraman
Distribution estimation under error-prone or non-ideal sampling modelled as "sticky" channels have been studied recently motivated by applications such as DNA computing. Missing ma…
Semi-supervised Active Regression
Fnu Devvrit, Nived Rajaraman, Pranjal Awasthi
Labelled data often comes at a high cost as it may require recruiting human labelers or running costly experiments. At the same time, in many practical scenarios, one already has a…
Provably Breaking the Quadratic Error Compounding Barrier in Imitation Learning, Optimally
Nived Rajaraman, Yanjun Han, Lin F. Yang +2
We study the statistical limits of Imitation Learning (IL) in episodic Markov Decision Processes (MDPs) with a state space . We focus on the known-transition setting w…
FastSecAgg: Scalable Secure Aggregation for Privacy-Preserving Federated Learning
Swanand Kadhe, Nived Rajaraman, O. Ozan Koyluoglu +1
Recent attacks on federated learning demonstrate that keeping the training data on clients' devices does not provide sufficient privacy, as the model parameters shared by clients c…
Toward the Fundamental Limits of Imitation Learning
Nived Rajaraman, Lin F. Yang, Jiantao Jiao +1
Imitation learning (IL) aims to mimic the behavior of an expert policy in a sequential decision-making problem given only demonstrations. In this paper, we focus on understanding t…