research
∙
04/25/2023
Sample-Specific Debiasing for Better Image-Text Models
Self-supervised representation learning on image-text data facilitates c...
share
research
∙
10/06/2022
SynBench: Task-Agnostic Benchmarking of Pretrained Representations using Synthetic Data
Recent success in fine-tuning large models, that are pretrained on broad...
research
∙
06/30/2022
Visual Pre-training for Navigation: What Can We Learn from Noise?
A powerful paradigm for sensorimotor control is to predict actions from ...
research
∙
12/08/2021
Revisiting Contrastive Learning through the Lens of Neighborhood Component Analysis: an Integrated Framework
As a seminal tool in self-supervised representation learning, contrastiv...
research
∙
10/13/2020
Higher-Order Certification for Randomized Smoothing
Randomized smoothing is a recently proposed defense against adversarial ...
research
∙
03/02/2020
Rethinking Randomized Smoothing for Adversarial Robustness
The fragility of modern machine learning models has drawn a considerable...
research
∙
02/28/2020
HOTCAKE: Higher Order Tucker Articulated Kernels for Deeper CNN Compression
The emerging edge computing has promoted immense interests in compacting...
research
∙
12/02/2019
Fastened CROWN: Tightened Neural Network Robustness Certificates
The rapid growth of deep learning applications in real life is accompani...
research
∙
05/17/2019
MiSC: Mixed Strategies Crowdsourcing
Popular crowdsourcing techniques mostly focus on evaluating workers' lab...
research
∙
05/17/2019
POPQORN: Quantifying Robustness of Recurrent Neural Networks
The vulnerability to adversarial attacks has been a critical issue for d...
research
∙
11/12/2018
Matrix Product Operator Restricted Boltzmann Machines
A restricted Boltzmann machine (RBM) learns a probability distribution o...
research
∙
11/09/2018
Deep Compression of Sum-Product Networks on Tensor Networks
Sum-product networks (SPNs) represent an emerging class of neural networ...
research
∙
04/17/2018
Fast and Accurate Tensor Completion with Total Variation Regularized Tensor Trains
We propose a new tensor completion method based on tensor trains. The to...
research
∙
04/17/2018
Fast and Accurate Tensor Completion with Tensor Trains: A System Identification Approach
We propose a novel tensor completion approach by equating it to a system...
research
∙
04/17/2018