Xiaoxia Wu
14 papers · 2019–2024 · 6 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
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Research topics
Machine Learning
(13)
Optimization & Theory Β· Machine Learning
(9)
Application Areas
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Deep Learning
(4)
Artificial Intelligence
(3)
Mathematics & Optimization
(3)
Natural Language Processing
(3)
Core AI
(3)
Optimization
(3)
Resources & Methods
(3)
Learning Paradigms
(2)
Learning Types
(2)
Optimization & Theory Β· Deep Learning
(2)
Techniques
(2)
Architectures
(1)
Keywords
model compression
(4)
linear convergence
(3)
weight quantization
(3)
stochastic gradient descent
(3)
non-convex optimization
(3)
deep learning
(2)
transformer model
(2)
gradient descent
(2)
knowledge distillation
(2)
post-training quantization
(2)
adaptive gradient
(2)
convergence rate
(2)
curriculum learning
(2)
large language model
(2)
model pretraining
(1)
efficient training
(1)
distributed learning
(1)
convergence analysis
(1)
robust optimization
(1)
model quantization
(1)
Papers
DeepSpeed Data Efficiency: Improving Deep Learning Model Quality and Training Efficiency via Efficient Data Sampling and Routing
AAAI 2024
Exploring Post-training Quantization in LLMs from Comprehensive Study to Low Rank Compensation
AAAI 2024
Found in the Middle: How Language Models Use Long Contexts Better via Plug-and-Play Positional Encoding
NeurIPS 2024
ZeRO++: Extremely Efficient Collective Communication for Large Model Training
ICLR 2024
Understanding Int4 Quantization for Language Models: Latency Speedup, Composability, and Failure Cases
ICML 2023
AdaLoss: A Computationally-Efficient and Provably Convergent Adaptive Gradient Method
AAAI 2022
XTC: Extreme Compression for Pre-trained Transformers Made Simple and Efficient
NeurIPS 2022
ZeroQuant: Efficient and Affordable Post-Training Quantization for Large-Scale Transformers
NeurIPS 2022
When Do Curricula Work?
ICLR 2021
AdaGrad stepsizes: Sharp convergence over nonconvex landscapes
JMLR 2020
Choosing the Sample with Lowest Loss makes SGD Robust
AISTATS 2020
Implicit Regularization and Convergence for Weight Normalization
NeurIPS 2020
Linear Convergence of Adaptive Stochastic Gradient Descent
AISTATS 2020
AdaGrad Stepsizes: Sharp Convergence Over Nonconvex Landscapes
ICML 2019