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09/15/2023
Adaptive Priority Reweighing for Generalizing Fairness Improvement
With the increasing penetration of machine learning applications in crit...
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08/29/2023
Heterogeneous Multi-Task Gaussian Cox Processes
This paper presents a novel extension of multi-task Gaussian Cox process...
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06/11/2023
E(2)-Equivariant Vision Transformer
Vision Transformer (ViT) has achieved remarkable performance in computer...
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06/05/2023
Decentralized SGD and Average-direction SAM are Asymptotically Equivalent
Decentralized stochastic gradient descent (D-SGD) allows collaborative l...
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05/23/2023
Improving Heterogeneous Model Reuse by Density Estimation
This paper studies multiparty learning, aiming to learn a model using th...
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02/22/2023
Learning to Generalize Provably in Learning to Optimize
Learning to optimize (L2O) has gained increasing popularity, which autom...
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01/19/2023
Global Nash Equilibrium in Non-convex Multi-player Game: Theory and Algorithms
Wide machine learning tasks can be formulated as non-convex multi-player...
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11/02/2022
Adversarial Auto-Augment with Label Preservation: A Representation Learning Principle Guided Approach
Data augmentation is a critical contributing factor to the success of de...
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10/15/2022
When to Update Your Model: Constrained Model-based Reinforcement Learning
Designing and analyzing model-based RL (MBRL) algorithms with guaranteed...
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10/11/2022
Benefits of Permutation-Equivariance in Auction Mechanisms
Designing an incentive-compatible auction mechanism that maximizes the a...
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10/04/2022
Bridged Transformer for Vision and Point Cloud 3D Object Detection
3D object detection is a crucial research topic in computer vision, whic...
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09/28/2022
InFi: End-to-End Learning to Filter Input for Resource-Efficiency in Mobile-Centric Inference
Mobile-centric AI applications have high requirements for resource-effic...
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08/30/2022
Super-model ecosystem: A domain-adaptation perspective
This paper attempts to establish the theoretical foundation for the emer...
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08/25/2022
Shortcut Learning of Large Language Models in Natural Language Understanding: A Survey
Large language models (LLMs) have achieved state-of-the-art performance ...
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06/25/2022
Topology-aware Generalization of Decentralized SGD
This paper studies the algorithmic stability and generalizability of dec...
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06/03/2022
Understanding deep learning via decision boundary
This paper discovers that the neural network with lower decision boundar...
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06/01/2022
DisPFL: Towards Communication-Efficient Personalized Federated Learning via Decentralized Sparse Training
Personalized federated learning is proposed to handle the data heterogen...
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04/25/2022
VITA: A Multi-Source Vicinal Transfer Augmentation Method for Out-of-Distribution Generalization
Invariance to diverse types of image corruption, such as noise, blurring...
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03/24/2022
Knowledge Removal in Sampling-based Bayesian Inference
The right to be forgotten has been legislated in many countries, but its...
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03/22/2022
Exploring High-Order Structure for Robust Graph Structure Learning
Recent studies show that Graph Neural Networks (GNNs) are vulnerable to ...
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01/27/2022
Achieving Personalized Federated Learning with Sparse Local Models
Federated learning (FL) is vulnerable to heterogeneously distributed dat...
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12/15/2021
Self-Ensembling GAN for Cross-Domain Semantic Segmentation
Deep neural networks (DNNs) have greatly contributed to the performance ...
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12/12/2021
Spatial-Temporal-Fusion BNN: Variational Bayesian Feature Layer
Bayesian neural networks (BNNs) have become a principal approach to alle...
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12/07/2021
Spectral Complexity-scaled Generalization Bound of Complex-valued Neural Networks
Complex-valued neural networks (CVNNs) have been widely applied to vario...
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12/04/2021
Channel Exchanging Networks for Multimodal and Multitask Dense Image Prediction
Multimodal fusion and multitask learning are two vital topics in machine...
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07/27/2021
Exploring Sequence Feature Alignment for Domain Adaptive Detection Transformers
Detection transformers have recently shown promising object detection re...
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01/16/2021
Bayesian Inference Forgetting
The right to be forgotten has been legislated in many countries but the ...
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01/14/2021
Neural networks behave as hash encoders: An empirical study
The input space of a neural network with ReLU-like activations is partit...
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12/25/2020
Robustness, Privacy, and Generalization of Adversarial Training
Adversarial training can considerably robustify deep neural networks to ...
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12/20/2020
Recent advances in deep learning theory
Deep learning is usually described as an experiment-driven field under c...
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11/12/2020
Artificial Neural Variability for Deep Learning: On Overfitting, Noise Memorization, and Catastrophic Forgetting
Deep learning is often criticized by two serious issues which rarely exi...
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07/18/2020
Tighter Generalization Bounds for Iterative Differentially Private Learning Algorithms
This paper studies the relationship between generalization and privacy p...
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03/27/2020
Piecewise linear activations substantially shape the loss surfaces of neural networks
Understanding the loss surface of a neural network is fundamentally impo...
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04/05/2019
Fast Spatio-Temporal Residual Network for Video Super-Resolution
Recently, deep learning based video super-resolution (SR) methods have a...
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04/02/2019
Why ResNet Works? Residuals Generalize
Residual connections significantly boost the performance of deep neural ...
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08/07/2018