b'Zhouchen Lin'

research

∙ 08/22/2023

ShadowNet for Data-Centric Quantum System Learning

Understanding the dynamics of large quantum systems is hindered by the c...

0 Yuxuan Du, et al. ∙

research

∙ 08/03/2023

Neural Collapse Terminus: A Unified Solution for Class Incremental Learning and Its Variants

How to enable learnability for new classes while keeping the capability ...

0 Yibo Yang, et al. ∙

research

∙ 06/21/2023

Task-Robust Pre-Training for Worst-Case Downstream Adaptation

Pre-training has achieved remarkable success when transferred to downstr...

0 Jianghui Wang, et al. ∙

research

∙ 05/29/2023

Code Prompting: a Neural Symbolic Method for Complex Reasoning in Large Language Models

Large language models (LLMs) have scaled up to unlock a wide range of co...

0 Yi Hu, et al. ∙

research

∙ 05/22/2023

Policy Representation via Diffusion Probability Model for Reinforcement Learning

Popular reinforcement learning (RL) algorithms tend to produce a unimoda...

0 Long Yang, et al. ∙

research

∙ 05/10/2023

Visual Tuning

Fine-tuning visual models has been widely shown promising performance on...

0 Bruce X. B. Yu, et al. ∙

research

∙ 03/17/2023

LION: Implicit Vision Prompt Tuning

Despite recent competitive performance across a range of vision tasks, v...

0 Haixin Wang, et al. ∙

research

∙ 03/08/2023

A Message Passing Perspective on Learning Dynamics of Contrastive Learning

In recent years, contrastive learning achieves impressive results on sel...

8 Yifei Wang, et al. ∙

research

∙ 02/28/2023

Towards Memory- and Time-Efficient Backpropagation for Training Spiking Neural Networks

Spiking Neural Networks (SNNs) are promising energy-efficient models for...

0 Qingyan Meng, et al. ∙

research

∙ 02/06/2023

Neural Collapse Inspired Feature-Classifier Alignment for Few-Shot Class Incremental Learning

Few-shot class-incremental learning (FSCIL) has been a challenging probl...

0 Yibo Yang, et al. ∙

research

∙ 02/01/2023

SPIDE: A Purely Spike-based Method for Training Feedback Spiking Neural Networks

Spiking neural networks (SNNs) with event-based computation are promisin...

0 Mingqing Xiao, et al. ∙

research

∙ 01/03/2023

PanopticPartFormer++: A Unified and Decoupled View for Panoptic Part Segmentation

Panoptic Part Segmentation (PPS) unifies panoptic segmentation and part ...

0 Xiangtai Li, et al. ∙

research

∙ 10/12/2022

Towards Theoretically Inspired Neural Initialization Optimization

Automated machine learning has been widely explored to reduce human effo...

0 Yibo Yang, et al. ∙

research

∙ 10/09/2022

Online Training Through Time for Spiking Neural Networks

Spiking neural networks (SNNs) are promising brain-inspired energy-effic...

0 Mingqing Xiao, et al. ∙

research

∙ 10/09/2022

Invertible Rescaling Network and Its Extensions

Image rescaling is a commonly used bidirectional operation, which first ...

0 Mingqing Xiao, et al. ∙

research

∙ 09/19/2022

Rethinking Knowledge Graph Evaluation Under the Open-World Assumption

Most knowledge graphs (KGs) are incomplete, which motivates one importan...

0 Haotong Yang, et al. ∙

research

∙ 08/13/2022

Adan: Adaptive Nesterov Momentum Algorithm for Faster Optimizing Deep Models

Adaptive gradient algorithms borrow the moving average idea of heavy bal...

0 Xingyu Xie, et al. ∙

research

∙ 08/07/2022

PDO-s3DCNNs: Partial Differential Operator Based Steerable 3D CNNs

Steerable models can provide very general and flexible equivariance by f...

0 Zhengyang Shen, et al. ∙

research

∙ 06/29/2022

Optimization-Induced Graph Implicit Nonlinear Diffusion

Due to the over-smoothing issue, most existing graph neural networks can...

3 Qi Chen, et al. ∙

research

∙ 06/20/2022

Two-Dimensional Weisfeiler-Lehman Graph Neural Networks for Link Prediction

Link prediction is one important application of graph neural networks (G...

11 Yang Hu, et al. ∙

research

∙ 05/27/2022

Global Convergence of Over-parameterized Deep Equilibrium Models

A deep equilibrium model (DEQ) is implicitly defined through an equilibr...

0 Zenan Ling, et al. ∙

research

∙ 05/26/2022

SymNMF-Net for The Symmetric NMF Problem

Recently, many works have demonstrated that Symmetric Non-negative Matri...

0 Mingjie Li, et al. ∙

research

∙ 05/01/2022

Training High-Performance Low-Latency Spiking Neural Networks by Differentiation on Spike Representation

Spiking Neural Network (SNN) is a promising energy-efficient AI model wh...

0 Qingyan Meng, et al. ∙

research

∙ 03/25/2022

Chaos is a Ladder: A New Theoretical Understanding of Contrastive Learning via Augmentation Overlap

Recently, contrastive learning has risen to be a promising approach for ...

6 Yifei Wang, et al. ∙

research

∙ 03/25/2022

A Unified Contrastive Energy-based Model for Understanding the Generative Ability of Adversarial Training

Adversarial Training (AT) is known as an effective approach to enhance t...

3 Yifei Wang, et al. ∙

research

∙ 03/17/2022

Do We Really Need a Learnable Classifier at the End of Deep Neural Network?

Modern deep neural networks for classification usually jointly learn a b...

1 Yibo Yang, et al. ∙

research

∙ 01/27/2022

Restarted Nonconvex Accelerated Gradient Descent: No More Polylogarithmic Factor in the O(ε^-7/4) Complexity

This paper studies the accelerated gradient descent for general nonconve...

0 Huan Li, et al. ∙

research

∙ 11/09/2021

On Training Implicit Models

This paper focuses on training implicit models of infinite layers. Speci...

8 Zhengyang Geng, et al. ∙

research

∙ 11/03/2021

Pareto Adversarial Robustness: Balancing Spatial Robustness and Sensitivity-based Robustness

Adversarial robustness, which mainly contains sensitivity-based robustne...

0 Ke Sun, et al. ∙

research

∙ 10/28/2021

Residual Relaxation for Multi-view Representation Learning

Multi-view methods learn representations by aligning multiple views of t...

4 Yifei Wang, et al. ∙

research

∙ 09/29/2021

Training Feedback Spiking Neural Networks by Implicit Differentiation on the Equilibrium State

Spiking neural networks (SNNs) are brain-inspired models that enable ene...

0 Mingqing Xiao, et al. ∙

research

∙ 09/09/2021

Is Attention Better Than Matrix Decomposition?

As an essential ingredient of modern deep learning, attention mechanism,...

47 Zhengyang Geng, et al. ∙

research

∙ 09/01/2021

Under-bagging Nearest Neighbors for Imbalanced Classification

In this paper, we propose an ensemble learning algorithm called under-ba...

0 Hanyuan Hang, et al. ∙

research

∙ 07/01/2021

Reparameterized Sampling for Generative Adversarial Networks

Recently, sampling methods have been successfully applied to enhance the...

0 Yifei Wang, et al. ∙

research

∙ 06/18/2021

Quantized Neural Networks via -1, +1 Encoding Decomposition and Acceleration

The training of deep neural networks (DNNs) always requires intensive re...

0 Qigong Sun, et al. ∙

research

∙ 06/10/2021

GBHT: Gradient Boosting Histogram Transform for Density Estimation

In this paper, we propose a density estimation algorithm called Gradient...

0 Jingyi Cui, et al. ∙

research

∙ 06/10/2021

Leveraged Weighted Loss for Partial Label Learning

As an important branch of weakly supervised learning, partial label lear...

0 Hongwei Wen, et al. ∙

research

∙ 06/03/2021

Gradient Boosted Binary Histogram Ensemble for Large-scale Regression

In this paper, we propose a gradient boosting algorithm for large-scale ...

0 Hanyuan Hang, et al. ∙

research

∙ 05/27/2021

Optimization Induced Equilibrium Networks

Implicit equilibrium models, i.e., deep neural networks (DNNs) defined b...

0 Xingyu Xie, et al. ∙

research

∙ 04/08/2021

PDO-eS^2CNNs: Partial Differential Operator Based Equivariant Spherical CNNs

Spherical signals exist in many applications, e.g., planetary data, LiDA...

0 Zhengyang Shen, et al. ∙

research

∙ 04/06/2021

Accelerated Gradient Tracking over Time-varying Graphs for Decentralized Optimization

Decentralized optimization over time-varying graphs has been increasingl...

0 Huan Li, et al. ∙

research

∙ 04/03/2021

Graph Contrastive Clustering

Recently, some contrastive learning methods have been proposed to simult...

0 Huasong Zhong, et al. ∙

research

∙ 03/11/2021

PointFlow: Flowing Semantics Through Points for Aerial Image Segmentation

Aerial Image Segmentation is a particular semantic segmentation problem ...

0 Xiangtai Li, et al. ∙

research

∙ 02/22/2021

Dissecting the Diffusion Process in Linear Graph Convolutional Networks

Graph Convolutional Networks (GCNs) have attracted more and more attenti...

0 Yifei Wang, et al. ∙

research

∙ 01/27/2021

Investigating Bi-Level Optimization for Learning and Vision from a Unified Perspective: A Survey and Beyond

Bi-Level Optimization (BLO) is originated from the area of economic game...

0 Risheng Liu, et al. ∙

research

∙ 01/27/2021

Towards Improving the Consistency, Efficiency, and Flexibility of Differentiable Neural Architecture Search

Most differentiable neural architecture search methods construct a super...

0 Yibo Yang, et al. ∙

research

∙ 12/10/2020

Learning Optimization-inspired Image Propagation with Control Mechanisms and Architecture Augmentations for Low-level Vision

In recent years, building deep learning models from optimization perspec...

3 Risheng Liu, et al. ∙

research

∙ 11/06/2020

Towards Efficient Scene Understanding via Squeeze Reasoning

Graph-based convolutional model such as non-local block has shown to be ...

7 Xiangtai Li, et al. ∙

research

∙ 10/13/2020

ISTA-NAS: Efficient and Consistent Neural Architecture Search by Sparse Coding

Neural architecture search (NAS) aims to produce the optimal sparse solu...

0 Yibo Yang, et al. ∙

research

∙ 09/09/2020

Variance Reduced EXTRA and DIGing and Their Optimal Acceleration for Strongly Convex Decentralized Optimization

We study stochastic decentralized optimization for the problem of traini...

0 Huan Li, et al. ∙

Zhouchen Lin

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