Felix Yu

25 papers · 2013–2025 · 8 conferences · across top CS/AI conferences

Achievements

🏃 Academic Marathon (12) 🗺️ Taxonomy Completionist (46) 🌈 Renaissance Researcher (7) 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (12) 🌍 Conference Polyglot (8) 🤝 Dynamic Duo (17) 🔥 Unstoppable (9) 💎 Century Club (25) 🚀 Conference Pioneer 📈 Trend Setter ⚡ Prolific Year (5) 🗃️ Keyword Collector (100)

Conferences

ICML (7) ICLR (6) ACL (3) AISTATS (3) EMNLP (2) NIPS (2) CVPR (1) IJCNLP (1)

Top co-authors

Sanjiv Kumar (17) Ankit Singh Rawat (6) Cho-jui Hsieh (6) MICHAL LUKASIK (5) Si Si (5) Ananda Theertha Suresh (4) Daniel Holtmann-Rice (3) Himanshu Jain (3) Aditya Menon (3) Inderjit S Dhillon (3)

Research topics

Differential Privacy (1)

Keywords

large language model (3) negative sampling (2) autoregressive sampling (2) large output space (2) language generation (2) federated learning (2) frame semantics (2) lexical constraint (2) bidirectional context (2) text infilling (2) representation learning (2) weakly supervised learning (1) compressed sensing (1) knowledge distillation (1) optimal transport (1) image retrieval (1) differential privacy (1) similarity search (1) mean estimation (1) embedding space (1)

Papers

Better autoregressive regression with LLMs via regression-aware fine-tuning ICLR 2025

Large Language Models are Interpretable Learners ICLR 2025

LoRA Done RITE: Robust Invariant Transformation Equilibration for LoRA Optimization ICLR 2025

Efficient and Asymptotically Unbiased Constrained Decoding for Large Language Models AISTATS 2025

Regression Aware Inference with LLMs EMNLP 2024

Automatic Engineering of Long Prompts ACL 2024

Two-stage LLM Fine-tuning with Less Specialization and More Generalization ICLR 2024

Serving Graph Compression for Graph Neural Networks ICLR 2023

Large Language Models with Controllable Working Memory ACL 2023

SpecTr: Fast Speculative Decoding via Optimal Transport NIPS 2023

FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning CVPR 2023

The Lazy Neuron Phenomenon: On Emergence of Activation Sparsity in Transformers ICLR 2023

Correlated Quantization for Distributed Mean Estimation and Optimization ICML 2022

InFillmore: Frame-Guided Language Generation with Bidirectional Context IJCNLP 2021

InFillmore: Frame-Guided Language Generation with Bidirectional Context ACL 2021

RankDistil: Knowledge Distillation for Ranking AISTATS 2021

Disentangling Sampling and Labeling Bias for Learning in Large-output Spaces ICML 2021

Semantic Label Smoothing for Sequence to Sequence Problems EMNLP 2020

Federated Learning with Only Positive Labels ICML 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 NIPS 2017

Circulant Binary Embedding ICML 2014

\proptoSVM for Learning with Label Proportions ICML 2013