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08/19/2023
FinEval: A Chinese Financial Domain Knowledge Evaluation Benchmark for Large Language Models
Large language models (LLMs) have demonstrated exceptional performance i...
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07/25/2023
Transfer Learning for Portfolio Optimization
In this work, we explore the possibility of utilizing transfer learning ...
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07/16/2023
MESOB: Balancing Equilibria Social Optimality
Motivated by bid recommendation in online ad auctions, this paper consid...
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05/22/2023
Feasibility of Transfer Learning: A Mathematical Framework
Transfer learning is a popular paradigm for utilizing existing knowledge...
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05/21/2023
Markov α-Potential Games: Equilibrium Approximation and Regret Analysis
This paper proposes a new framework to study multi-agent interaction in ...
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05/17/2023
On Consistency of Signatures Using Lasso
Signature transforms are iterated path integrals of continuous and discr...
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04/17/2023
MFGLib: A Library for Mean-Field Games
Mean-field games (MFGs) are limiting models to approximate N-player game...
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01/27/2023
Feasibility and Transferability of Transfer Learning: A Mathematical Framework
Transfer learning is an emerging and popular paradigm for utilizing exis...
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09/25/2022
Capacity dependent analysis for functional online learning algorithms
This article provides convergence analysis of online stochastic gradient...
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06/20/2022
MF-OMO: An Optimization Formulation of Mean-Field Games
Theory of mean-field games (MFGs) has recently experienced an exponentia...
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02/11/2022
Meta-learning with GANs for anomaly detection, with deployment in high-speed rail inspection system
Anomaly detection has been an active research area with a wide range of ...
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01/04/2022
Transfer Learning for Retinal Vascular Disease Detection: A Pilot Study with Diabetic Retinopathy and Retinopathy of Prematurity
Retinal vascular diseases affect the well-being of human body and someti...
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12/17/2021
SiamTrans: Zero-Shot Multi-Frame Image Restoration with Pre-Trained Siamese Transformers
We propose a novel zero-shot multi-frame image restoration method for re...
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12/05/2021
Extracting and Measuring Uncertain Biomedical Knowledge from Scientific Statements
Purpose: This study aims to develop a novel approach to extracting and m...
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12/01/2021
Convergence of GANs Training: A Game and Stochastic Control Methodology
Training of generative adversarial networks (GANs) is known for its diff...
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11/22/2021
A General Framework for Lifelong Localization and Mapping in Changing Environment
The environment of most real-world scenarios such as malls and supermark...
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09/13/2021
Theoretical Guarantees of Fictitious Discount Algorithms for Episodic Reinforcement Learning and Global Convergence of Policy Gradient Methods
When designing algorithms for finite-time-horizon episodic reinforcement...
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08/20/2021
FedSkel: Efficient Federated Learning on Heterogeneous Systems with Skeleton Gradients Update
Federated learning aims to protect users' privacy while performing data ...
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08/05/2021
Mean-Field Multi-Agent Reinforcement Learning: A Decentralized Network Approach
One of the challenges for multi-agent reinforcement learning (MARL) is d...
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06/07/2021
RoSearch: Search for Robust Student Architectures When Distilling Pre-trained Language Models
Pre-trained language models achieve outstanding performance in NLP tasks...
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05/17/2021
An SDE Framework for Adversarial Training, with Convergence and Robustness Analysis
Adversarial training has gained great popularity as one of the most effe...
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04/29/2021
Discriminative-Generative Dual Memory Video Anomaly Detection
Recently, people tried to use a few anomalies for video anomaly detectio...
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04/25/2021
Generative Adversarial Network: Some Analytical Perspectives
Ever since its debut, generative adversarial networks (GANs) have attrac...
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04/19/2021
Reinforcement learning for linear-convex models with jumps via stability analysis of feedback controls
We study finite-time horizon continuous-time linear-convex reinforcement...
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01/27/2021
Edge-Labeling based Directed Gated Graph Network for Few-shot Learning
Existing graph-network-based few-shot learning methods obtain similarity...
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09/30/2020
Entropy Regularization for Mean Field Games with Learning
Entropy regularization has been extensively adopted to improve the effic...
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09/17/2020
DanceIt: Music-inspired Dancing Video Synthesis
Close your eyes and listen to music, one can easily imagine an actor dan...
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09/16/2020
Kernel-based L_2-Boosting with Structure Constraints
Developing efficient kernel methods for regression is very popular in th...
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06/16/2020
PAC-Bayesian Generalization Bounds for MultiLayer Perceptrons
We study PAC-Bayesian generalization bounds for Multilayer Perceptrons (...
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06/12/2020
Early Detection of Retinopathy of Prematurity (ROP) in Retinal Fundus Images Via Convolutional Neural Networks
Retinopathy of prematurity (ROP) is an abnormal blood vessel development...
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06/03/2020
Approximation and convergence of GANs training: an SDE approach
Generative adversarial networks (GANs) have enjoyed tremendous empirical...
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05/09/2020
Perturbed gradient descent with occupation time
This paper develops further the idea of perturbed gradient descent, by a...
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03/13/2020
A General Framework for Learning Mean-Field Games
This paper presents a general mean-field game (GMFG) framework for simul...
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02/20/2020
Audio-video Emotion Recognition in the Wild using Deep Hybrid Networks
This paper presents an audiovisual-based emotion recognition hybrid netw...
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02/10/2020
Q-Learning for Mean-Field Controls
Multi-agent reinforcement learning (MARL) has been applied to many chall...
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02/10/2020
Connecting GANs and MFGs
Generative Adversarial Networks (GANs), introduced in 2014 [12], have ce...
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10/17/2019
Consistency of the Buckley-Osthus model and the hierarchical preferential attachment model
This paper is concerned with statistical estimation of two preferential ...
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10/02/2019
Automatic Group Cohesiveness Detection With Multi-modal Features
Group cohesiveness is a compelling and often studied composition in grou...
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05/06/2019
POG: Personalized Outfit Generation for Fashion Recommendation at Alibaba iFashion
Increasing demand for fashion recommendation raises a lot of challenges ...
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10/22/2018
Sparsemax and Relaxed Wasserstein for Topic Sparsity
Topic sparsity refers to the observation that individual documents usual...
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10/06/2018
Consistency and Computation of Regularized MLEs for Multivariate Hawkes Processes
This paper proves the consistency property for the regularized maximum l...
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05/23/2017
Ambiguity set and learning via Bregman and Wasserstein
Construction of ambiguity set in robust optimization relies on the choic...
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05/19/2017
Relaxed Wasserstein with Applications to GANs
We propose a novel class of statistical divergences called Relaxed Wasse...
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08/11/2016
Distributed learning with regularized least squares
We study distributed learning with the least squares regularization sche...
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05/28/2012