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← Authors

Hsiang-Fu Yu

25 papers · 2014–2024 · 7 conferences · across top CS/AI conferences

Achievements

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+10 more ↓ 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (11) 🧭 Keyword Pioneer 🌍 Conference Polyglot (7)
🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (14) 🌍 Conference Polyglot (7) 🀝 Dynamic Duo (16) πŸ† Keyword Champion (2) πŸ’Ž Century Club (25) ⚑ Prolific Year (5) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (132) πŸ”₯ Unstoppable (11)

Conferences

NIPS (10) ICML (6) AISTATS (4) NAACL (2) ACL (1) ICLR (1) JMLR (1)

Top co-authors

Cho-jui Hsieh (16) Inderjit S Dhillon (11) Jiong Zhang (7) Wei-Cheng Chang (7) Inderjit Dhillon (6) Inderjit S. Dhillon (6) Eli Chien (3) Nikhil Rao (3) Olgica Milenkovic (2) Jyun-Yu Jiang (2)

Keywords

matrix factorization (6) multi-label classification (4) extreme multi-label classification (4) linear convergence (3) collaborative filtering (3) coordinate descent (3) data augmentation (2) model compression (2) stochastic optimization (2) high-dimensional time series (2) parallel optimization (2) empirical risk minimization (2) demand forecasting (2) maximum inner product search (2) self-supervised learning (1) few-shot learning (1) feature selection (1) logistic regression (1) zero-shot learning (1) text classification (1)

Papers

MinPrompt: Graph-based Minimal Prompt Data Augmentation for Few-shot Question Answering ACL 2024 Representer Point Selection for Explaining Regularized High-dimensional Models ICML 2023 PINA: Leveraging Side Information in eXtreme Multi-label Classification via Predicted Instance Neighborhood Aggregation ICML 2023 Extreme Zero-Shot Learning for Extreme Text Classification NAACL 2022 Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction ICLR 2022 PECOS: Prediction for Enormous and Correlated Output Spaces JMLR 2022 ELIAS: End-to-End Learning to Index and Search in Large Output Spaces NIPS 2022 Label Disentanglement in Partition-based Extreme Multilabel Classification NIPS 2021 DRONE: Data-aware Low-rank Compression for Large NLP Models NIPS 2021 Fast Multi-Resolution Transformer Fine-tuning for Extreme Multi-label Text Classification NIPS 2021 Graph DNA: Deep Neighborhood Aware Graph Encoding for Collaborative Filtering AISTATS 2020 Learning to Encode Position for Transformer with Continuous Dynamical Model ICML 2020 Extreme Multi-label Classification from Aggregated Labels ICML 2020 Parallel Asynchronous Stochastic Coordinate Descent with Auxiliary Variables AISTATS 2019 Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting NIPS 2019 AutoAssist: A Framework to Accelerate Training of Deep Neural Networks NIPS 2019 Extreme Stochastic Variational Inference: Distributed Inference for Large Scale Mixture Models AISTATS 2019 A Fast Sampling Algorithm for Maximum Inner Product Search AISTATS 2019 Learning Word Embeddings for Low-Resource Languages by PU Learning NAACL 2018 A Greedy Approach for Budgeted Maximum Inner Product Search NIPS 2017 Temporal Regularized Matrix Factorization for High-dimensional Time Series Prediction NIPS 2016 Asynchronous Parallel Greedy Coordinate Descent NIPS 2016 Collaborative Filtering with Graph Information: Consistency and Scalable Methods NIPS 2015 PASSCoDe: Parallel ASynchronous Stochastic dual Co-ordinate Descent ICML 2015 Large-scale Multi-label Learning with Missing Labels ICML 2014