Arya Mazumdar

Multilabel Classification by Hierarchical Partitioning and Data-dependent Grouping

2020 · arXiv (Cornell University)

In modern multilabel classification problems, each data instance belongs to a small number of classes from a large set of classes. In other words, these problems involve learning very sparse binary label vectors. Moreover, in …

Session-Aware Query Auto-completion using Extreme Multi-Label Ranking

2021

Query auto-completion (QAC) is a fundamental feature in search engines where the task is to suggest plausible completions of a prefix typed in the search bar. Previous queries in the user session can provide useful …

Support Recovery in Mixture Models with Sparse Parameters

2022 · arXiv (Cornell University)

Mixture models are widely used to fit complex and multimodal datasets. In this paper we study mixtures with high dimensional sparse latent parameter vectors and consider the problem of support recovery of those vectors. While …

On the Theory of Continual Learning with Gradient Descent for Neural Networks

2025 · arXiv (Cornell University)

Continual learning, the ability of a model to adapt to an ongoing sequence of tasks without forgetting earlier ones, is a central goal of artificial intelligence. To better understand its underlying mechanisms, we study the …