Xiaohan Chen | DeepAI

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139 publications
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123 publications
Yuan Xie
118 publications
Sijia Liu
112 publications
fcq
109 publications
Zhe Gan
102 publications
richb
90 publications
Tianlong Chen
82 publications

∙ 05/29/2023

Towards Constituting Mathematical Structures for Learning to Optimize

Learning to Optimize (L2O), a technique that utilizes machine learning t...

0 Jialin Liu, et al. ∙

∙ 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. ∙

∙ 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. ∙

∙ 12/18/2021

Federated Dynamic Sparse Training: Computing Less, Communicating Less, Yet Learning Better

Federated learning (FL) enables distribution of machine learning workloa...

0 Sameer Bibikar, et al. ∙

∙ 10/29/2021

Hyperparameter Tuning is All You Need for LISTA

Learned Iterative Shrinkage-Thresholding Algorithm (LISTA) introduces th...

11 Xiaohan Chen, et al. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 04/08/2021

A Design Space Study for LISTA and Beyond

In recent years, great success has been witnessed in building problem-sp...

0 Tianjian Meng, et al. ∙

∙ 03/30/2021

The Elastic Lottery Ticket Hypothesis

Lottery Ticket Hypothesis raises keen attention to identifying sparse tr...

0 Xiaohan Chen, et al. ∙

∙ 03/23/2021

Learning to Optimize: A Primer and A Benchmark

Learning to optimize (L2O) is an emerging approach that leverages machin...

61 Tianlong Chen, et al. ∙

∙ 01/04/2021

SmartDeal: Re-Modeling Deep Network Weights for Efficient Inference and Training

The record-breaking performance of deep neural networks (DNNs) comes wit...

5 Xiaohan Chen, et al. ∙

∙ 12/31/2020

EarlyBERT: Efficient BERT Training via Early-bird Lottery Tickets

Deep, heavily overparameterized language models such as BERT, XLNet and ...

0 Xiaohan Chen, et al. ∙

∙ 10/24/2020

ShiftAddNet: A Hardware-Inspired Deep Network

Multiplication (e.g., convolution) is arguably a cornerstone of modern d...

0 Haoran You, et al. ∙

∙ 05/07/2020

SmartExchange: Trading Higher-cost Memory Storage/Access for Lower-cost Computation

We present SmartExchange, an algorithm-hardware co-design framework to t...

6 fcq, et al. ∙

∙ 03/04/2020

Safeguarded Learned Convex Optimization

Many applications require repeatedly solving a certain type of optimizat...

0 Howard Heaton, et al. ∙

∙ 10/29/2019

E2-Train: Energy-Efficient Deep Network Training with Data-, Model-, and Algorithm-Level Saving

Convolutional neural networks (CNNs) have been increasingly deployed to ...

0 Yue Wang, et al. ∙

∙ 09/26/2019

Drawing early-bird tickets: Towards more efficient training of deep networks

(Frankle & Carbin, 2019) shows that there exist winning tickets (small b...

0 Haoran You, et al. ∙

∙ 05/14/2019

Plug-and-Play Methods Provably Converge with Properly Trained Denoisers

Plug-and-play (PnP) is a non-convex framework that integrates modern den...

9 Ernest K. Ryu, et al. ∙

∙ 10/22/2018

Can We Gain More from Orthogonality Regularizations in Training Deep CNNs?

This paper seeks to answer the question: as the (near-) orthogonality of...

0 Nitin Bansal, et al. ∙

∙ 08/29/2018

Theoretical Linear Convergence of Unfolded ISTA and its Practical Weights and Thresholds

In recent years, unfolding iterative algorithms as neural networks has b...

5 Xiaohan Chen, et al. ∙

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