357 citations · 1.3k across the 33 of their papers we have counts for
5 papers · 1 filter
Context-Aware Bandits
Shuai Li, Purushottam Kar
We propose an efficient Context-Aware clustering of Bandits (CAB) algorithm, which can capture collaborative effects. CAB can be easily deployed in a real-world recommendation syst…
Locally Non-linear Embeddings for Extreme Multi-label Learning
Kush Bhatia, Himanshu Jain, Purushottam Kar +2
The objective in extreme multi-label learning is to train a classifier that can automatically tag a novel data point with the most relevant subset of labels from an extremely large…
Robust Regression via Hard Thresholding
Kush Bhatia, Prateek Jain, Purushottam Kar
We study the problem of Robust Least Squares Regression (RLSR) where several response variables can be adversarially corrupted. More specifically, for a data matrix X \in R^{p x n}…
Surrogate Functions for Maximizing Precision at the Top
Purushottam Kar, Harikrishna Narasimhan, Prateek Jain
The problem of maximizing precision at the top of a ranked list, often dubbed Precision@k (prec@k), finds relevance in myriad learning applications such as ranking, multi-label cla…
Optimizing Non-decomposable Performance Measures: A Tale of Two Classes
Harikrishna Narasimhan, Purushottam Kar, Prateek Jain
Modern classification problems frequently present mild to severe label imbalance as well as specific requirements on classification characteristics, and require optimizing performa…