Prateek Jain

Scalable Optimization of Multivariate Performance Measures in Multi-instance Multi-label Learning

2017 · Proceedings of the AAAI Conference on Artificial Intelligence

The problem of multi-instance multi-label learning (MIML) requires a bag of instances to be assigned a set of labels most relevant to the bag as a whole. The problem finds numerous applications in machine learning, …

Learning Accurate Decision Trees with Bandit Feedback via Quantized Gradient Descent

2021 · arXiv (Cornell University)

Decision trees provide a rich family of highly non-linear but efficient models, due to which they continue to be the go-to family of predictive models by practitioners across domains. But learning trees is challenging due …

Distributional Semantics Meets Multi-Label Learning

2019 · Proceedings of the AAAI Conference on Artificial Intelligence

We present a label embedding based approach to large-scale multi-label learning, drawing inspiration from ideas rooted in distributional semantics, specifically the Skip Gram Negative Sampling (SGNS) approach, widely used to learn word embeddings. Besides leading …