research
∙
09/14/2023
An Interactive Framework for Profiling News Media Sources
The recent rise of social media has led to the spread of large amounts o...
share
research
∙
06/13/2023
Better Generalization with Semantic IDs: A case study in Ranking for Recommendations
Training good representations for items is critical in recommender model...
research
∙
05/10/2023
Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Prediction
Large Language Models (LLMs) have demonstrated exceptional capabilities ...
research
∙
04/21/2023
Improving Grounded Language Understanding in a Collaborative Environment by Interacting with Agents Through Help Feedback
Many approaches to Natural Language Processing (NLP) tasks often treat t...
research
∙
10/23/2022
Pushing the Efficiency Limit Using Structured Sparse Convolutions
Weight pruning is among the most popular approaches for compressing deep...
research
∙
10/17/2022
Pseudo-OOD training for robust language models
While pre-trained large-scale deep models have garnered attention as an ...
research
∙
09/19/2021
A two-step machine learning approach for crop disease detection: an application of GAN and UAV technology
Automated plant diagnosis is a technology that promises large increases ...
research
∙
03/25/2021
Efficient Feature Transformations for Discriminative and Generative Continual Learning
As neural networks are increasingly being applied to real-world applicat...
research
∙
02/23/2021
Meta-Learned Attribute Self-Gating for Continual Generalized Zero-Shot Learning
Zero-shot learning (ZSL) has been shown to be a promising approach to ge...
research
∙
10/23/2020
Counterfactual Representation Learning with Balancing Weights
A key to causal inference with observational data is achieving balance i...
research
∙
08/13/2020
WAFFLe: Weight Anonymized Factorization for Federated Learning
In domains where data are sensitive or private, there is great value in ...
research
∙
04/21/2020
Bayesian Nonparametric Weight Factorization for Continual Learning
Naively trained neural networks tend to experience catastrophic forgetti...
research
∙
02/29/2020
Survival Cluster Analysis
Conventional survival analysis approaches estimate risk scores or indivi...
research
∙
05/14/2019
Stochastic Blockmodels meet Graph Neural Networks
Stochastic blockmodels (SBM) and their variants, e.g., mixed-membership ...
research
∙
05/12/2019
