252 citations · 435 across the 19 of their papers we have counts for
7 papers · 1 filter
Understanding the Effect of the Long Tail on Neural Network Compression
Harvey Dam, Vinu Joseph, Aditya Bhaskara +3
Network compression is now a mature sub-field of neural network research: over the last decade, significant progress has been made towards reducing the size of models and speeding…
Logarithmic Regret from Sublinear Hints
Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar +1
We consider the online linear optimization problem, where at every step the algorithm plays a point in the unit ball, and suffers loss for some cost…
Online Linear Optimization with Many Hints
Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar +1
We study an online linear optimization (OLO) problem in which the learner is provided access to "hint" vectors in each round prior to making a decision. In this setting, we dev…
Fair clustering via equitable group representations
Mohsen Abbasi, Aditya Bhaskara, Suresh Venkatasubramanian
What does it mean for a clustering to be fair? One popular approach seeks to ensure that each cluster contains groups in (roughly) the same proportion in which they exist in the po…
Online Learning with Imperfect Hints
Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar +1
We consider a variant of the classical online linear optimization problem in which at every step, the online player receives a "hint" vector before choosing the action for that rou…
Approximate Guarantees for Dictionary Learning
Aditya Bhaskara, Wai Ming Tai
In the dictionary learning (or sparse coding) problem, we are given a collection of signals (vectors in ), and the goal is to find a "basis" in which the signals have…
Provable Bounds for Learning Some Deep Representations
Sanjeev Arora, Aditya Bhaskara, Rong Ge +1
We give algorithms with provable guarantees that learn a class of deep nets in the generative model view popularized by Hinton and others. Our generative model is an node multi…