Hyokun Yun

According to our database, Hyokun Yun authored at least 23 papers between 2011 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Exposing Privacy Gaps: Membership Inference Attack on Preference Data for LLM Alignment.

Qizhang Feng, Siva Rajesh Kasa, Hyokun Yun, Choon Hui Teo, Sravan Babu Bodapati

CoRR, 2024

Robust Multi-Task Learning with Excess Risks.

Yifei He, Shiji Zhou, Guojun Zhang, Hyokun Yun, Yi Xu, Belinda Zeng, Trishul Chilimbi, Han Zhao

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Threshold-aware Learning to Generate Feasible Solutions for Mixed Integer Programs.

Taehyun Yoon, Jinwon Choi, Hyokun Yun, Sungbin Lim

CoRR, 2023

2022

MICO: Selective Search with Mutual Information Co-training.

Zhanyu Wang, Xiao Zhang, Hyokun Yun, Choon Hui Teo, Trishul Chilimbi

Proceedings of the 29th International Conference on Computational Linguistics, 2022

2021

A Deep Reinforcement Learning Approach for Solving the Traveling Salesman Problem with Drone.

Aigerim Bogyrbayeva, Taehyun Yoon, Hanbum Ko, Sungbin Lim, Hyokun Yun, Changhyun Kwon

CoRR, 2021

2020

Tiering as a Stochastic Submodular Optimization Problem.

Hyokun Yun, Michael Froh, Roshan Makhijani, Brian Luc, Alex Smola, Trishul Chilimbi

CoRR, 2020

2019

Scaling Multinomial Logistic Regression via Hybrid Parallelism.

Parameswaran Raman, Sriram Srinivasan, Shin Matsushima, Xinhua Zhang, Hyokun Yun, S. V. N. Vishwanathan

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Robustness to Capitalization Errors in Named Entity Recognition.

Sravan Babu Bodapati, Hyokun Yun, Yaser Al-Onaizan

Proceedings of the 5th Workshop on Noisy User-generated Text, 2019

2017

Deep Active Learning for Named Entity Recognition.

Yanyao Shen, Hyokun Yun, Zachary Chase Lipton, Yakov Kronrod, Animashree Anandkumar

Proceedings of the 2nd Workshop on Representation Learning for NLP, 2017

Distributed Stochastic Optimization of Regularized Risk via Saddle-Point Problem.

Shin Matsushima, Hyokun Yun, Xinhua Zhang, S. V. N. Vishwanathan

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

2016

DS-MLR: Exploiting Double Separability for Scaling up Distributed Multinomial Logistic Regression.

Parameswaran Raman, Shin Matsushima, Xinhua Zhang, Hyokun Yun, S. V. N. Vishwanathan

CoRR, 2016

Nomadic Computing for Big Data Analytics.

Hsiang-Fu Yu, Cho-Jui Hsieh, Hyokun Yun, S. V. N. Vishwanathan, Inderjit S. Dhillon

Computer, 2016

WordRank: Learning Word Embeddings via Robust Ranking.

Shihao Ji, Hyokun Yun, Pinar Yanardag, Shin Matsushima, S. V. N. Vishwanathan

Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, 2016

2015

A Scalable Asynchronous Distributed Algorithm for Topic Modeling.

Hsiang-Fu Yu, Cho-Jui Hsieh, Hyokun Yun, S. V. N. Vishwanathan, Inderjit S. Dhillon

Proceedings of the 24th International Conference on World Wide Web, 2015

2014

NOMAD: Nonlocking, stOchastic Multi-machine algorithm for Asynchronous and Decentralized matrix completion.

Hyokun Yun, Hsiang-Fu Yu, Cho-Jui Hsieh, S. V. N. Vishwanathan, Inderjit S. Dhillon

Proc. VLDB Endow., 2014

Ranking via Robust Binary Classification and Parallel Parameter Estimation in Large-Scale Data.

Hyokun Yun, Parameswaran Raman, S. V. N. Vishwanathan

CoRR, 2014

Distributed Stochastic Optimization of the Regularized Risk.

Shin Matsushima, Hyokun Yun, S. V. N. Vishwanathan

CoRR, 2014

Ranking via Robust Binary Classification.

Hyokun Yun, Parameswaran Raman, S. V. N. Vishwanathan

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013

NOMAD: Non-locking, stOchastic Multi-machine algorithm for Asynchronous and Decentralized matrix completion.

Hyokun Yun, Hsiang-Fu Yu, Cho-Jui Hsieh, S. V. N. Vishwanathan, Inderjit S. Dhillon

CoRR, 2013

2012

Quilting Stochastic Kronecker Product Graphs to Generate Multiplicative Attribute Graphs.

Hyokun Yun, S. V. N. Vishwanathan

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Efficiently Sampling Multiplicative Attribute Graphs Using a Ball-Dropping Process

Hyokun Yun, S. V. N. Vishwanathan

CoRR, 2012

How to filter out random clickers in a crowdsourcing-based study?

Sung-Hee Kim, Hyokun Yun, Ji Soo Yi

Proceedings of the 2012 BELIV Workshop: Beyond Time and Errors, 2012

2011

Using Logistic Regression to Analyze the Balance of a Game: The Case of StarCraft II

Hyokun Yun

CoRR, 2011