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06/24/2023
High-dimensional outlier detection and variable selection via adaptive weighted mean regression
This paper proposes an adaptive penalized weighted mean regression for o...
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06/17/2023
Online Local Differential Private Quantile Inference via Self-normalization
Based on binary inquiries, we developed an algorithm to estimate populat...
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02/05/2023
Scalable inference in functional linear regression with streaming data
Traditional static functional data analysis is facing new challenges due...
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10/31/2022
Class Interference of Deep Neural Networks
Recognizing and telling similar objects apart is even hard for human bei...
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10/17/2022
Identification, Amplification and Measurement: A bridge to Gaussian Differential Privacy
Gaussian differential privacy (GDP) is a single-parameter family of priv...
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10/05/2022
Conformalized Fairness via Quantile Regression
Algorithmic fairness has received increased attention in socially sensit...
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09/29/2022
How Does Value Distribution in Distributional Reinforcement Learning Help Optimization?
We consider the problem of learning a set of probability distributions f...
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05/20/2022
Sigmoidally Preconditioned Off-policy Learning:a new exploration method for reinforcement learning
One of the major difficulties of reinforcement learning is learning from...
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02/01/2022
Distributional Reinforcement Learning via Sinkhorn Iterations
Distributional reinforcement learning (RL) is a class of state-of-the-ar...
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12/17/2021
Functional Linear Regression for Partially Observed Functional Data
In the functional linear regression model, many methods have been propos...
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12/09/2021
Word Embeddings via Causal Inference: Gender Bias Reducing and Semantic Information Preserving
With widening deployments of natural language processing (NLP) in daily ...
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10/17/2021
Damped Anderson Mixing for Deep Reinforcement Learning: Acceleration, Convergence, and Stabilization
Anderson mixing has been heuristically applied to reinforcement learning...
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10/07/2021
Towards Understanding Distributional Reinforcement Learning: Regularization, Optimization, Acceleration and Sinkhorn Algorithm
Distributional reinforcement learning (RL) is a class of state-of-the-ar...
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05/31/2021
Meta-HAR: Federated Representation Learning for Human Activity Recognition
Human activity recognition (HAR) based on mobile sensors plays an import...
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04/27/2018
Negative Log Likelihood Ratio Loss for Deep Neural Network Classification
In deep neural network, the cross-entropy loss function is commonly used...
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09/13/2017
