Xiaohan Chen
28 papers · 2018–2025 · 8 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (8) π Academic Marathon (7) π§ Keyword Pioneer π Interdisciplinary Bridge π Cross-Pollinator (13)
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(13)
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(5)
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(44)
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Dynamic Duo
(26)
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Triple Crown
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(92)
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Unstoppable
(8)
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Century Club
(28)
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Prolific Year
(8)
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Trend Setter
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The Questioner
(2)
Conferences
NIPS (11)
ICLR (8)
ICML (3)
AAAI (2)
ACL (1)
AISTATS (1)
IJCNLP (1)
JMLR (1)
Top co-authors
Keywords
model compression
(6)
lottery ticket hypothesis
(3)
network pruning
(3)
convolutional neural network
(2)
neural network
(2)
efficient computing
(2)
hyperparameter tuning
(2)
learning to optimize
(2)
sparse recovery
(2)
sparse training
(2)
few-shot learning
(1)
universal approximation
(1)
attention mechanism
(1)
deep learning
(1)
neural network training
(1)
uncertainty quantification
(1)
non-iid learning
(1)
compressive sensing
(1)
continuous optimization
(1)
out-of-distribution generalization
(1)
Papers
Expressive Power of Graph Neural Networks for (Mixed-Integer) Quadratic Programs
ICML 2025
Rethinking the Capacity of Graph Neural Networks for Branching Strategy
NIPS 2024
Safeguarded Learned Convex Optimization
AAAI 2023
More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity
ICLR 2023
Towards Constituting Mathematical Structures for Learning to Optimize
ICML 2023
The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training
ICLR 2022
Peek-a-Boo: What (More) is Disguised in a Randomly Weighted Neural Network, and How to Find It Efficiently
ICLR 2022
Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity
ICLR 2022
Randomized Channel Shuffling: Minimal-Overhead Backdoor Attack Detection without Clean Datasets
NIPS 2022
Federated Dynamic Sparse Training: Computing Less, Communicating Less, Yet Learning Better
AAAI 2022
Learning to Optimize: A Primer and A Benchmark
JMLR 2022
Learning A Minimax Optimizer: A Pilot Study
ICLR 2021
Hyperparameter Tuning is All You Need for LISTA
NIPS 2021
EarlyBERT: Efficient BERT Training via Early-bird Lottery Tickets
ACL 2021
Sparse Training via Boosting Pruning Plasticity with Neuroregeneration
NIPS 2021
EarlyBERT: Efficient BERT Training via Early-bird Lottery Tickets
IJCNLP 2021
The Elastic Lottery Ticket Hypothesis
NIPS 2021
A Design Space Study for LISTA and Beyond
ICLR 2021
Sanity Checks for Lottery Tickets: Does Your Winning Ticket Really Win the Jackpot?
NIPS 2021
Uncertainty Quantification for Deep Context-Aware Mobile Activity Recognition and Unknown Context Discovery
AISTATS 2020
ShiftAddNet: A Hardware-Inspired Deep Network
NIPS 2020
MATE: Plugging in Model Awareness to Task Embedding for Meta Learning
NIPS 2020
Drawing Early-Bird Tickets: Toward More Efficient Training of Deep Networks
ICLR 2020
Plug-and-Play Methods Provably Converge with Properly Trained Denoisers
ICML 2019
ALISTA: Analytic Weights Are As Good As Learned Weights in LISTA
ICLR 2019
E2-Train: Training State-of-the-art CNNs with Over 80% Energy Savings
NIPS 2019
Can We Gain More from Orthogonality Regularizations in Training Deep Networks?
NIPS 2018
Theoretical Linear Convergence of Unfolded ISTA and Its Practical Weights and Thresholds
NIPS 2018