114 citations · 199 across the 23 of their papers we have counts for
7 papers · 1 filter
Labels in Extremes: How Well Calibrated are Extreme Multi-label Classifiers?
Nasib Ullah, Erik Schultheis, Jinbin Zhang +1
Extreme multilabel classification (XMLC) problems occur in settings such as related product recommendation, large-scale document tagging, or ad prediction, and are characterized by…
Navigating Extremes: Dynamic Sparsity in Large Output Spaces
Nasib Ullah, Erik Schultheis, Mike Lasby +2
In recent years, Dynamic Sparse Training (DST) has emerged as an alternative to post-training pruning for generating efficient models. In principle, DST allows for a more memory ef…
A General Online Algorithm for Optimizing Complex Performance Metrics
Wojciech Kotłowski, Marek Wydmuch, Erik Schultheis +2
We consider sequential maximization of performance metrics that are general functions of a confusion matrix of a classifier (such as precision, F-measure, or G-mean). Such metrics…
Large Language Model as a Teacher for Zero-shot Tagging at Extreme Scales
Jinbin Zhang, Nasib Ullah, Rohit Babbar
Extreme Multi-label Text Classification (XMC) entails selecting the most relevant labels for an instance from a vast label set. Extreme Zero-shot XMC (EZ-XMC) extends this challeng…
Learning label-label correlations in Extreme Multi-label Classification via Label Features
Siddhant Kharbanda, Devaansh Gupta, Erik Schultheis +3
Extreme Multi-label Text Classification (XMC) involves learning a classifier that can assign an input with a subset of most relevant labels from millions of label choices. Recent w…
UniDEC : Unified Dual Encoder and Classifier Training for Extreme Multi-Label Classification
Siddhant Kharbanda, Devaansh Gupta, Gururaj K +4
Extreme Multi-label Classification (XMC) involves predicting a subset of relevant labels from an extremely large label space, given an input query and labels with textual features.…
Consistent algorithms for multi-label classification with macro-at- metrics
Erik Schultheis, Wojciech Kotłowski, Marek Wydmuch +3
We consider the optimization of complex performance metrics in multi-label classification under the population utility framework. We mainly focus on metrics linearly decomposable i…