research
∙
07/11/2023
Monotone deep Boltzmann machines
Deep Boltzmann machines (DBMs), one of the first “deep” learning methods...
share
research
∙
07/10/2023
Leveraging Multiple Descriptive Features for Robust Few-shot Image Learning
Modern image classification is based upon directly predicting model clas...
research
∙
10/27/2021
Learning-Augmented k-means Clustering
k-means clustering is a well-studied problem due to its wide applicabili...
research
∙
06/16/2021
Non-PSD Matrix Sketching with Applications to Regression and Optimization
A variety of dimensionality reduction techniques have been applied for c...
research
∙
06/12/2021
Provable Adaptation across Multiway Domains via Representation Learning
This paper studies zero-shot domain adaptation where each domain is inde...
research
∙
12/27/2019
Strong Coresets for Subspace Approximation and k-Median in Nearly Linear Time
Recently the first (1+ϵ)-approximate strong coresets for k-median and su...
research
∙
06/12/2019
A Structured Learning Approach to Temporal Relation Extraction
Identifying temporal relations between events is an essential step towar...
research
∙
06/12/2019
Joint Reasoning for Temporal and Causal Relations
Understanding temporal and causal relations between events is a fundamen...
research
∙
06/12/2019
CogCompTime: A Tool for Understanding Time in Natural Language Text
Automatic extraction of temporal information in text is an important com...
research
∙
05/08/2019
Does Data Augmentation Lead to Positive Margin?
Data augmentation (DA) is commonly used during model training, as it sig...
research
∙
04/01/2018
