activity
20212026
most citedLearning to Optimize: A Primer and A Benchmark

91 citations · 193 across the 13 of their papers we have counts for

collaborators

13 papers

cs.LO2026

Lean Refactor: Multi-Objective Controllable Proof Optimization via Agentic Strategy Search

Jialin Lu, Soonho Kong, Rodrigo Stehling +4

We present Lean Refactor, a plug-and-play retrieval-augmented agentic framework for multi-objective, controllable, and version-robust refactoring of Lean proofs. LLM-generated proo…

cs.LG2024

Principled Architecture-aware Scaling of Hyperparameters

Wuyang Chen, Junru Wu, Zhangyang Wang +1

Training a high-quality deep neural network requires choosing suitable hyperparameters, which is a non-trivial and expensive process. Current works try to automatically optimize or…

cs.CV2022★ 3 cited

Data-Model-Circuit Tri-Design for Ultra-Light Video Intelligence on Edge Devices

Yimeng Zhang, Akshay Karkal Kamath, Qiucheng Wu +6

In this paper, we propose a data-model-hardware tri-design framework for high-throughput, low-cost, and high-accuracy multi-object tracking (MOT) on High-Definition (HD) video stre…

cs.LG2022★ 3 cited

Deep Architecture Connectivity Matters for Its Convergence: A Fine-Grained Analysis

Wuyang Chen, Wei Huang, Xinyu Gong +2

Advanced deep neural networks (DNNs), designed by either human or AutoML algorithms, are growing increasingly complex. Diverse operations are connected by complicated connectivity…

cs.LG2022★ 7 cited

Auto-scaling Vision Transformers without Training

Wuyang Chen, Wei Huang, Xianzhi Du +3

This work targets automated designing and scaling of Vision Transformers (ViTs). The motivation comes from two pain spots: 1) the lack of efficient and principled methods for desig…

cs.CV2021★ 12 cited

A Simple Single-Scale Vision Transformer for Object Localization and Instance Segmentation

Wuyang Chen, Xianzhi Du, Fan Yang +8

This work presents a simple vision transformer design as a strong baseline for object localization and instance segmentation tasks. Transformers recently demonstrate competitive pe…

cs.CV2021

Font Completion and Manipulation by Cycling Between Multi-Modality Representations

Ye Yuan, Wuyang Chen, Zhaowen Wang +4

Generating font glyphs of consistent style from one or a few reference glyphs, i.e., font completion, is an important task in topographical design. As the problem is more well-defi…

cs.LG2021★ 7 cited

Understanding and Accelerating Neural Architecture Search with Training-Free and Theory-Grounded Metrics

Wuyang Chen, Xinyu Gong, Junru Wu +5

This work targets designing a principled and unified training-free framework for Neural Architecture Search (NAS), with high performance, low cost, and in-depth interpretation. NAS…

cs.CV2021

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

Chaojian Li, Wuyang Chen, Yuchen Gu +4

Semantic segmentation for scene understanding is nowadays widely demanded, raising significant challenges for the algorithm efficiency, especially its applications on resource-limi…

cs.CV2021★ 18 cited

Contrastive Syn-to-Real Generalization

Wuyang Chen, Zhiding Yu, Shalini De Mello +4

Training on synthetic data can be beneficial for label or data-scarce scenarios. However, synthetically trained models often suffer from poor generalization in real domains due to…

cs.CV2021★ 51 cited

Neural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired Perspective

Wuyang Chen, Xinyu Gong, Zhangyang Wang

Neural Architecture Search (NAS) has been explosively studied to automate the discovery of top-performer neural networks. Current works require heavy training of supernet or intens…

math.OC2021★ 91 cited

Learning to Optimize: A Primer and A Benchmark

Tianlong Chen, Xiaohan Chen, Wuyang Chen +4

Learning to optimize (L2O) is an emerging approach that leverages machine learning to develop optimization methods, aiming at reducing the laborious iterations of hand engineering.…

cs.CV2021★ 1 cited

Sandwich Batch Normalization: A Drop-In Replacement for Feature Distribution Heterogeneity

Xinyu Gong, Wuyang Chen, Tianlong Chen +1

We present Sandwich Batch Normalization (SaBN), a frustratingly easy improvement of Batch Normalization (BN) with only a few lines of code changes. SaBN is motivated by addressing…