Hsiang-Fu Yu
25 papers · 2014–2024 · 7 venues · across top CS/AI venues
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Achievements
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(5)
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Dynamic Duo
(16)
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Renaissance Researcher
(5)
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Century Club Β· Bronze
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Keyword Collector
(136)
Top co-authors
Research topics
Machine Learning
(23)
Core Methods
(15)
Optimization & Theory Β· Machine Learning
(11)
Deep Learning
(7)
Learning Types Β· Machine Learning
(7)
Mathematics & Optimization
(6)
Optimization
(6)
Data Science & Analytics
(5)
Natural Language Processing
(5)
Application Areas
(5)
Learning Types Β· Deep Learning
(4)
Artificial Intelligence
(3)
Applications Β· Data Science & Analytics
(3)
Applications Β· Natural Language Processing
(3)
Optimization & Theory Β· Deep Learning
(3)
Keywords
matrix factorization
(6)
extreme multi-label classification
(5)
multi-label classification
(5)
linear convergence
(3)
coordinate descent
(3)
collaborative filtering
(3)
maximum inner product search
(2)
model compression
(2)
empirical risk minimization
(2)
parallel optimization
(2)
support vector machine
(2)
high-dimensional time series
(2)
low-rank approximation
(2)
stochastic optimization
(2)
self-supervised learning
(2)
demand forecasting
(2)
data augmentation
(2)
feature selection
(1)
link prediction
(1)
logistic regression
(1)
Papers
MinPrompt: Graph-based Minimal Prompt Data Augmentation for Few-shot Question Answering
ACL 2024
PINA: Leveraging Side Information in eXtreme Multi-label Classification via Predicted Instance Neighborhood Aggregation
ICML 2023
Representer Point Selection for Explaining Regularized High-dimensional Models
ICML 2023
ELIAS: End-to-End Learning to Index and Search in Large Output Spaces
NeurIPS 2022
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
DRONE: Data-aware Low-rank Compression for Large NLP Models
NeurIPS 2021
Fast Multi-Resolution Transformer Fine-tuning for Extreme Multi-label Text Classification
NeurIPS 2021
Label Disentanglement in Partition-based Extreme Multilabel Classification
NeurIPS 2021
Extreme Multi-label Classification from Aggregated Labels
ICML 2020
Graph DNA: Deep Neighborhood Aware Graph Encoding for Collaborative Filtering
AISTATS 2020
Learning to Encode Position for Transformer with Continuous Dynamical Model
ICML 2020
A Fast Sampling Algorithm for Maximum Inner Product Search
AISTATS 2019
AutoAssist: A Framework to Accelerate Training of Deep Neural Networks
NeurIPS 2019
Extreme Stochastic Variational Inference: Distributed Inference for Large Scale Mixture Models
AISTATS 2019
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
NeurIPS 2019
Learning Word Embeddings for Low-Resource Languages by PU Learning
NAACL 2018
A Greedy Approach for Budgeted Maximum Inner Product Search
NeurIPS 2017
Asynchronous Parallel Greedy Coordinate Descent
NeurIPS 2016
Temporal Regularized Matrix Factorization for High-dimensional Time Series Prediction
NeurIPS 2016
Collaborative Filtering with Graph Information: Consistency and Scalable Methods
NeurIPS 2015
PASSCoDe: Parallel ASynchronous Stochastic dual Co-ordinate Descent
ICML 2015
Large-scale Multi-label Learning with Missing Labels
ICML 2014