research
∙
11/23/2022
Representation Learning for Continuous Action Spaces is Beneficial for Efficient Policy Learning
Deep reinforcement learning (DRL) breaks through the bottlenecks of trad...
share
research
∙
10/31/2022
Cost-aware Generalized α-investing for Multiple Hypothesis Testing
We consider the problem of sequential multiple hypothesis testing with n...
research
∙
05/24/2022
Exploiting Dynamic and Fine-grained Semantic Scope for Extreme Multi-label Text Classification
Extreme multi-label text classification (XMTC) refers to the problem of ...
research
∙
06/13/2021
Deep Bayesian Unsupervised Lifelong Learning
Lifelong Learning (LL) refers to the ability to continually learn and so...
research
∙
07/18/2019
A Computer Vision Application for Assessing Facial Acne Severity from Selfie Images
We worked with Nestle Skin Health SHIELD (Skin Health, Innovation, Educa...
research
∙
06/07/2019
Adaptive Nonparametric Variational Autoencoder
Clustering is used to find structure in unlabeled data by grouping simil...
research
∙
05/30/2019
Analysis of high-dimensional Continuous Time Markov Chains using the Local Bouncy Particle Sampler
Sampling the parameters of high-dimensional Continuous Time Markov Chain...
research
∙
05/24/2019
Deep-gKnock: nonlinear group-feature selection with deep neural network
Feature selection is central to contemporary high-dimensional data analy...
research
∙
06/11/2018
Simulation Study on a New Peer Review Approach
The increasing volume of scientific publications and grant proposals has...
research
∙
07/19/2013
Model-Based Policy Gradients with Parameter-Based Exploration by Least-Squares Conditional Density Estimation
The goal of reinforcement learning (RL) is to let an agent learn an opti...
research
∙
01/17/2013