16 citations · 46 across the 7 of their papers we have counts for
9 papers
BOReFT: Manifold Steering of Language Models for Black-box Optimization
Dhruv Agarwal, Rico Angell, Kavitha Srinivas +4
Language models are increasingly used as proposal models for black-box search, from program optimization to molecular design. Existing approaches typically improve proposals throug…
Fast, Scalable, Warm-Start Semidefinite Programming with Spectral Bundling and Sketching
Rico Angell, Andrew McCallum
While semidefinite programming (SDP) has traditionally been limited to moderate-sized problems, recent algorithms augmented with matrix sketching techniques have enabled solving la…
Efficient Nearest Neighbor Search for Cross-Encoder Models using Matrix Factorization
Nishant Yadav, Nicholas Monath, Rico Angell +2
Efficient k-nearest neighbor search is a fundamental task, foundational for many problems in NLP. When the similarity is measured by dot-product between dual-encoder vectors or $\e…
Entity Linking and Discovery via Arborescence-based Supervised Clustering
Dhruv Agarwal, Rico Angell, Nicholas Monath +1
Previous work has shown promising results in performing entity linking by measuring not only the affinities between mentions and entities but also those amongst mentions. In this p…
Relation Matters in Sampling: A Scalable Multi-Relational Graph Neural Network for Drug-Drug Interaction Prediction
Arthur Feeney, Rishabh Gupta, Veronika Thost +4
Sampling is an established technique to scale graph neural networks to large graphs. Current approaches however assume the graphs to be homogeneous in terms of relations and ignore…
Low Resource Recognition and Linking of Biomedical Concepts from a Large Ontology
Sunil Mohan, Rico Angell, Nick Monath +1
Tools to explore scientific literature are essential for scientists, especially in biomedicine, where about a million new papers are published every year. Many such tools provide u…
Fairkit, Fairkit, on the Wall, Who's the Fairest of Them All? Supporting Data Scientists in Training Fair Models
Brittany Johnson, Jesse Bartola, Rico Angell +4
Modern software relies heavily on data and machine learning, and affects decisions that shape our world. Unfortunately, recent studies have shown that because of biases in data, so…
Clustering-based Inference for Biomedical Entity Linking
Rico Angell, Nicholas Monath, Sunil Mohan +2
Due to large number of entities in biomedical knowledge bases, only a small fraction of entities have corresponding labelled training data. This necessitates entity linking models…
Don't Be Greedy: Leveraging Community Structure to Find High Quality Seed Sets for Influence Maximization
Rico Angell, Grant Schoenebeck
We consider the problem of maximizing the spread of influence in a social network by choosing a fixed number of initial seeds --- a central problem in the study of network cascades…