Felix Yu
24 papers · 2013–2025 · 7 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (53) π Academic Marathon Β· Half π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Dynamic Duo
(17)
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Keyword Champion
(2)
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Keyword Pioneer
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Renaissance Researcher
(5)
π₯
Unstoppable Β· Bronze
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Prolific Year Β· Productive
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Conference Pioneer
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Century Club Β· Bronze
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Trend Setter
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Keyword Collector
(126)
Top co-authors
Research topics
Machine Learning
(20)
Core Methods
(11)
Optimization & Theory
(9)
Artificial Intelligence
(8)
Deep Learning
(8)
Natural Language Processing
(8)
Core AI
(7)
Mathematics & Optimization
(6)
Application Areas
(6)
Learning Types Β· Machine Learning
(6)
Resources & Methods
(6)
Optimization
(5)
Learning Types Β· Deep Learning
(4)
Learning Paradigms
(3)
Architectures
(2)
Keywords
large language model
(5)
large output space
(3)
autoregressive sampling
(2)
constrained decoding
(2)
representation learning
(2)
federated learning
(2)
language model
(2)
negative sampling
(2)
multi-class classification
(2)
image retrieval
(1)
similarity search
(1)
embedding space
(1)
dimensionality reduction
(1)
optimal transport
(1)
differential privacy
(1)
transfer learning
(1)
machine translation
(1)
iterative optimization
(1)
transformer architecture
(1)
knowledge editing
(1)
Papers
Better autoregressive regression with LLMs via regression-aware fine-tuning
ICLR 2025
Efficient and Asymptotically Unbiased Constrained Decoding for Large Language Models
AISTATS 2025
Large Language Models are Interpretable Learners
ICLR 2025
LoRA Done RITE: Robust Invariant Transformation Equilibration for LoRA Optimization
ICLR 2025
Automatic Engineering of Long Prompts
ACL 2024
Regression Aware Inference with LLMs
EMNLP 2024
Two-stage LLM Fine-tuning with Less Specialization and More Generalization
ICLR 2024
FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning
CVPR 2023
Large Language Models with Controllable Working Memory
ACL 2023
Serving Graph Compression for Graph Neural Networks
ICLR 2023
SpecTr: Fast Speculative Decoding via Optimal Transport
NeurIPS 2023
The Lazy Neuron Phenomenon: On Emergence of Activation Sparsity in Transformers
ICLR 2023
Correlated Quantization for Distributed Mean Estimation and Optimization
ICML 2022
Disentangling Sampling and Labeling Bias for Learning in Large-output Spaces
ICML 2021
InFillmore: Frame-Guided Language Generation with Bidirectional Context
ACL 2021
RankDistil: Knowledge Distillation for Ranking
AISTATS 2021
Federated Learning with Only Positive Labels
ICML 2020
Semantic Label Smoothing for Sequence to Sequence Problems
EMNLP 2020
Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling
ICML 2019
Stochastic Negative Mining for Learning with Large Output Spaces
AISTATS 2019
Loss Decomposition for Fast Learning in Large Output Spaces
ICML 2018
Multiscale Quantization for Fast Similarity Search
NeurIPS 2017
Circulant Binary Embedding
ICML 2014
\proptoSVM for Learning with Label Proportions
ICML 2013