b'Tianlong Chen'

research

∙ 08/22/2023

Enhancing NeRF akin to Enhancing LLMs: Generalizable NeRF Transformer with Mixture-of-View-Experts

Cross-scene generalizable NeRF models, which can directly synthesize nov...

0 Wenyan Cong, et al. ∙

research

∙ 08/19/2023

Robust Mixture-of-Expert Training for Convolutional Neural Networks

Sparsely-gated Mixture of Expert (MoE), an emerging deep model architect...

0 Yihua Zhang, et al. ∙

research

∙ 06/25/2023

Enhancing Adversarial Training via Reweighting Optimization Trajectory

Despite the fact that adversarial training has become the de facto metho...

0 Tianjin Huang, et al. ∙

research

∙ 06/24/2023

H_2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models

Large Language Models (LLMs), despite their recent impressive accomplish...

0 Zhenyu Zhang, et al. ∙

research

∙ 06/18/2023

Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication

Graphs are omnipresent and GNNs are a powerful family of neural networks...

0 Ajay Jaiswal, et al. ∙

research

∙ 06/18/2023

Instant Soup: Cheap Pruning Ensembles in A Single Pass Can Draw Lottery Tickets from Large Models

Large pre-trained transformers have been receiving explosive attention i...

0 Ajay Jaiswal, et al. ∙

research

∙ 06/06/2023

The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter

Large pre-trained transformers are show-stealer in modern-day deep learn...

0 Ajay Jaiswal, et al. ∙

research

∙ 03/03/2023

Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together!

Sparse Neural Networks (SNNs) have received voluminous attention predomi...

0 Shiwei Liu, et al. ∙

research

∙ 03/02/2023

Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers

Despite their remarkable achievement, gigantic transformers encounter si...

0 Tianlong Chen, et al. ∙

research

∙ 02/28/2023

M-L2O: Towards Generalizable Learning-to-Optimize by Test-Time Fast Self-Adaptation

Learning to Optimize (L2O) has drawn increasing attention as it often re...

0 Junjie Yang, et al. ∙

research

∙ 02/22/2023

Learning to Generalize Provably in Learning to Optimize

Learning to optimize (L2O) has gained increasing popularity, which autom...

0 Junjie Yang, et al. ∙

research

∙ 12/06/2022

Attend Who is Weak: Pruning-assisted Medical Image Localization under Sophisticated and Implicit Imbalances

Deep neural networks (DNNs) have rapidly become a de facto choice for me...

0 Ajay Jaiswal, et al. ∙

research

∙ 11/28/2022

You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets

Recent works have impressively demonstrated that there exists a subnetwo...

12 Tianjin Huang, et al. ∙

research

∙ 10/26/2022

M^3ViT: Mixture-of-Experts Vision Transformer for Efficient Multi-task Learning with Model-Accelerator Co-design

Multi-task learning (MTL) encapsulates multiple learned tasks in a singl...

0 Hanxue Liang, et al. ∙

research

∙ 10/14/2022

Old can be Gold: Better Gradient Flow can Make Vanilla-GCNs Great Again

Despite the enormous success of Graph Convolutional Networks (GCNs) in m...

0 Ajay Jaiswal, et al. ∙

research

∙ 10/14/2022

A Comprehensive Study on Large-Scale Graph Training: Benchmarking and Rethinking

Large-scale graph training is a notoriously challenging problem for grap...

0 Keyu Duan, et al. ∙

research

∙ 10/08/2022

Advancing Model Pruning via Bi-level Optimization

The deployment constraints in practical applications necessitate the pru...

9 Yihua Zhang, et al. ∙

research

∙ 10/07/2022

Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative

This paper targets at improving the generalizability of hypergraph neura...

3 Tianxin Wei, et al. ∙

research

∙ 09/15/2022

Can We Solve 3D Vision Tasks Starting from A 2D Vision Transformer?

Vision Transformers (ViTs) have proven to be effective, in solving 2D im...

8 Yi Wang, et al. ∙

research

∙ 07/27/2022

Is Attention All NeRF Needs?

We present Generalizable NeRF Transformer (GNT), a pure, unified transfo...

0 Mukund Varma T, et al. ∙

research

∙ 07/08/2022

Neural Implicit Dictionary via Mixture-of-Expert Training

Representing visual signals by coordinate-based deep fully-connected net...

0 Peihao Wang, et al. ∙

research

∙ 07/07/2022

More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity

Transformers have quickly shined in the computer vision world since the ...

11 Shiwei Liu, et al. ∙

research

∙ 07/04/2022

Aug-NeRF: Training Stronger Neural Radiance Fields with Triple-Level Physically-Grounded Augmentations

Neural Radiance Field (NeRF) regresses a neural parameterized scene by d...

0 Tianlong Chen, et al. ∙

research

∙ 06/15/2022

Queried Unlabeled Data Improves and Robustifies Class-Incremental Learning

Class-incremental learning (CIL) suffers from the notorious dilemma betw...

9 Tianlong Chen, et al. ∙

research

∙ 06/15/2022

Linearity Grafting: Relaxed Neuron Pruning Helps Certifiable Robustness

Certifiable robustness is a highly desirable property for adopting deep ...

4 Tianlong Chen, et al. ∙

research

∙ 06/15/2022

Can pruning improve certified robustness of neural networks?

With the rapid development of deep learning, the sizes of neural network...

5 Zhangheng Li, et al. ∙

research

∙ 05/24/2022

Quarantine: Sparsity Can Uncover the Trojan Attack Trigger for Free

Trojan attacks threaten deep neural networks (DNNs) by poisoning them to...

4 Tianlong Chen, et al. ∙

research

∙ 04/04/2022

APP: Anytime Progressive Pruning

With the latest advances in deep learning, there has been a lot of focus...

0 Diganta Misra, et al. ∙

research

∙ 03/13/2022

Symbolic Learning to Optimize: Towards Interpretability and Scalability

Recent studies on Learning to Optimize (L2O) suggest a promising path to...

0 Wenqing Zheng, et al. ∙

research

∙ 03/12/2022

Optimizer Amalgamation

Selecting an appropriate optimizer for a given problem is of major inter...

11 Tianshu Huang, et al. ∙

research

∙ 03/12/2022

The Principle of Diversity: Training Stronger Vision Transformers Calls for Reducing All Levels of Redundancy

Vision transformers (ViTs) have gained increasing popularity as they are...

0 Tianlong Chen, et al. ∙

research

∙ 03/09/2022

Anti-Oversmoothing in Deep Vision Transformers via the Fourier Domain Analysis: From Theory to Practice

Vision Transformer (ViT) has recently demonstrated promise in computer v...

0 Peihao Wang, et al. ∙

research

∙ 03/05/2022

Don't Be So Dense: Sparse-to-Sparse GAN Training Without Sacrificing Performance

Generative adversarial networks (GANs) have received an upsurging intere...

0 Shiwei Liu, et al. ∙

research

∙ 02/09/2022

Coarsening the Granularity: Towards Structurally Sparse Lottery Tickets

The lottery ticket hypothesis (LTH) has shown that dense models contain ...

3 Tianlong Chen, et al. ∙

research

∙ 02/05/2022

The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training

Random pruning is arguably the most naive way to attain sparsity in neur...

7 Shiwei Liu, et al. ∙

research

∙ 01/04/2022

Bringing Your Own View: Graph Contrastive Learning without Prefabricated Data Augmentations

Self-supervision is recently surging at its new frontier of graph learni...

5 Yuning You, et al. ∙

research

∙ 11/01/2021

Improving Contrastive Learning on Imbalanced Seed Data via Open-World Sampling

Contrastive learning approaches have achieved great success in learning ...

0 Ziyu Jiang, et al. ∙

research

∙ 10/30/2021

You are caught stealing my winning lottery ticket! Making a lottery ticket claim its ownership

Despite tremendous success in many application scenarios, the training a...

0 Xuxi Chen, et al. ∙

research

∙ 10/30/2021

DSEE: Dually Sparsity-embedded Efficient Tuning of Pre-trained Language Models

Gigantic pre-trained models have become central to natural language proc...

0 Xuxi Chen, et al. ∙

research

∙ 10/28/2021

CAP: Co-Adversarial Perturbation on Weights and Features for Improving Generalization of Graph Neural Networks

Despite the recent advances of graph neural networks (GNNs) in modeling ...

0 Haotian Xue, et al. ∙

research

∙ 10/09/2021

Towards Lifelong Learning of Multilingual Text-To-Speech Synthesis

This work presents a lifelong learning approach to train a multilingual ...

12 Mu Yang, et al. ∙

research

∙ 10/07/2021

Universality of Deep Neural Network Lottery Tickets: A Renormalization Group Perspective

Foundational work on the Lottery Ticket Hypothesis has suggested an exci...

0 William T Redman, et al. ∙

research

∙ 08/24/2021

Bag of Tricks for Training Deeper Graph Neural Networks: A Comprehensive Benchmark Study

Training deep graph neural networks (GNNs) is notoriously hard. Besides ...

0 Tianlong Chen, et al. ∙

research

∙ 07/16/2021

DANCE: DAta-Network Co-optimization for Efficient Segmentation Model Training and Inference

Semantic segmentation for scene understanding is nowadays widely demande...

0 Chaojian Li, et al. ∙

research

∙ 07/01/2021

Sanity Checks for Lottery Tickets: Does Your Winning Ticket Really Win the Jackpot?

There have been long-standing controversies and inconsistencies over the...

2 Xiaolong Ma, et al. ∙

research

∙ 06/28/2021

FreeTickets: Accurate, Robust and Efficient Deep Ensemble by Training with Dynamic Sparsity

Recent works on sparse neural networks have demonstrated that it is poss...

16 Shiwei Liu, et al. ∙

research

∙ 06/24/2021

Scalable Perception-Action-Communication Loops with Convolutional and Graph Neural Networks

In this paper, we present a perception-action-communication loop design ...

0 Ting-Kuei Hu, et al. ∙

research

∙ 06/19/2021

Sparse Training via Boosting Pruning Plasticity with Neuroregeneration

Works on lottery ticket hypothesis (LTH) and single-shot network pruning...

5 Shiwei Liu, et al. ∙

research

∙ 06/10/2021

Sparse and Imperceptible Adversarial Attack via a Homotopy Algorithm

Sparse adversarial attacks can fool deep neural networks (DNNs) by only ...

0 Mingkang Zhu, et al. ∙

research

∙ 06/08/2021

Chasing Sparsity in Vision Transformers: An End-to-End Exploration

Vision transformers (ViTs) have recently received explosive popularity, ...

0 Tianlong Chen, et al. ∙

Tianlong Chen

Featured Co-authors