Yucheng Lu
13 papers · 2020–2025 · 5 conferences · across top CS/AI conferences
Achievements
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🐝 Cross-Pollinator (9) 🏃 Academic Marathon (5) 🧭 Keyword Pioneer 🌍 Conference Polyglot (5) 🌈 Renaissance Researcher (6)
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Conference Polyglot
(5)
🏃
Academic Marathon
(5)
👑
Triple Crown
🗃️
Keyword Collector
(57)
⚡
Prolific Year
(5)
💎
Century Club
(13)
❓
The Questioner
Conferences
ICML (5)
NIPS (3)
ACL (2)
ICLR (2)
JMLR (1)
Top co-authors
Keywords
stochastic gradient descent
(5)
distributed training
(3)
non-convex optimization
(3)
distributed learning
(3)
model compression
(2)
stochastic optimization
(2)
gradient balancing
(2)
gossip algorithm
(2)
decentralized learning
(2)
large language model
(2)
iteration complexity
(2)
variance estimation
(1)
variance reduction
(1)
time series forecasting
(1)
text classification
(1)
stratified sampling
(1)
convergence rate
(1)
distributed optimization
(1)
random search
(1)
parallel machine learning
(1)
Papers
Tracking Green Industrial Policies with LLMs: A Demonstration
ACL 2025
Can Reasoning LLMs Synthesize Complex Climate Statements?
ACL 2025
Decentralized Learning: Theoretical Optimality and Practical Improvements
JMLR 2023
Coordinating Distributed Example Orders for Provably Accelerated Training
NIPS 2023
Maximizing Communication Efficiency for Large-scale Training via 0/1 Adam
ICLR 2023
STEP: Learning N:M Structured Sparsity Masks from Scratch with Precondition
ICML 2023
CocktailSGD: Fine-tuning Foundation Models over 500Mbps Networks
ICML 2023
GraB: Finding Provably Better Data Permutations than Random Reshuffling
NIPS 2022
A General Analysis of Example-Selection for Stochastic Gradient Descent
ICLR 2022
Optimal Complexity in Decentralized Training
ICML 2021
Variance Reduced Training with Stratified Sampling for Forecasting Models
ICML 2021
Hyperparameter Optimization Is Deceiving Us, and How to Stop It
NIPS 2021
Moniqua: Modulo Quantized Communication in Decentralized SGD
ICML 2020