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06/08/2022
What-Is and How-To for Fairness in Machine Learning: A Survey, Reflection, and Perspective
Algorithmic fairness has attracted increasing attention in the machine l...
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03/30/2022
Factored Adaptation for Non-Stationary Reinforcement Learning
Dealing with non-stationarity in environments (i.e., transition dynamics...
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03/29/2022
Sample Recycling for Nested Simulation with Application in Portfolio Risk Measurement
Nested simulation is a natural approach to tackle nested estimation prob...
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12/13/2021
GLaM: Efficient Scaling of Language Models with Mixture-of-Experts
Scaling language models with more data, compute and parameters has drive...
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11/05/2021
Transferable Time-Series Forecasting under Causal Conditional Shift
This paper focuses on the problem of semi-supervised domain adaptation f...
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07/06/2021
AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning
Most approaches in reinforcement learning (RL) are data-hungry and speci...
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06/05/2021
Conditional Contrastive Learning: Removing Undesirable Information in Self-Supervised Representations
Self-supervised learning is a form of unsupervised learning that leverag...
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04/27/2021
A Survey on Neural Recommendation: From Collaborative Filtering to Content and Context Enriched Recommendation
Influenced by the stunning success of deep learning in computer vision a...
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02/28/2021
RIS-Aided Wireless Communications: Prototyping, Adaptive Beamforming, and Indoor/Outdoor Field Trials
The prospects of using a Reconfigurable Intelligent Surface (RIS) to aid...
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12/22/2020
Learning Disentangled Semantic Representation for Domain Adaptation
Domain adaptation is an important but challenging task. Most of the exis...
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04/12/2018
Causal Generative Domain Adaptation Networks
We propose a new generative model for domain adaptation, in which traini...
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06/10/2017
