Se-Young Yun

Orcid: 0000-0001-6675-5113

Affiliations:
  • Korea Advanced Institute of Science and Technology (KAIST), Graduate School of AI Korea, Daejeon, South Korea
  • Los Alamos National Laboratory, NM, USA
  • Microsoft Research, Cambridge, UK
  • Microsoft Research-INRIA Joint Centre, Paris, France
  • KTH Royal Institute of Technology, Stockholm, Sweden


According to our database1, Se-Young Yun authored at least 150 papers between 2009 and 2024.

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Bibliography

2024
Optimal clustering from noisy binary feedback.
Mach. Learn., May, 2024

Diffusion-based Episodes Augmentation for Offline Multi-Agent Reinforcement Learning.
CoRR, 2024

VACoDe: Visual Augmented Contrastive Decoding.
CoRR, 2024

A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits.
CoRR, 2024

Learning Video Temporal Dynamics with Cross-Modal Attention for Robust Audio-Visual Speech Recognition.
CoRR, 2024

BAPO: Base-Anchored Preference Optimization for Personalized Alignment in Large Language Models.
CoRR, 2024

Block Transformer: Global-to-Local Language Modeling for Fast Inference.
CoRR, 2024

FedDr+: Stabilizing Dot-regression with Global Feature Distillation for Federated Learning.
CoRR, 2024

Preference Alignment with Flow Matching.
CoRR, 2024

Why In-Context Learning Transformers are Tabular Data Classifiers.
CoRR, 2024

Towards Unbiased Evaluation of Detecting Unanswerable Questions in EHRSQL.
CoRR, 2024

Rotting Infinitely Many-armed Bandits beyond the Worst-case Rotting: An Adaptive Approach.
CoRR, 2024

Non-linear Fusion in Federated Learning: A Hypernetwork Approach to Federated Domain Generalization.
CoRR, 2024

Revisiting Early-Learning Regularization When Federated Learning Meets Noisy Labels.
CoRR, 2024

Carpe diem: On the Evaluation of World Knowledge in Lifelong Language Models.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

Fine-tuning Pre-trained Models for Robustness under Noisy Labels.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

DistiLLM: Towards Streamlined Distillation for Large Language Models.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Synergistic Integration of Coordinate Network and Tensorial Feature for Improving Neural Radiance Fields from Sparse Inputs.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Instructive Decoding: Instruction-Tuned Large Language Models are Self-Refiner from Noisy Instructions.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Towards Fast Multilingual LLM Inference: Speculative Decoding and Specialized Drafters.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Towards Difficulty-Agnostic Efficient Transfer Learning for Vision-Language Models.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

BAPO: Base-Anchored Preference Optimization for Overcoming Forgetting in Large Language Models Personalization.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Stable Language Model Pre-training by Reducing Embedding Variability.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

FedSOL: Stabilized Orthogonal Learning with Proximal Restrictions in Federated Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Improved Regret Bounds of (Multinomial) Logistic Bandits via Regret-to-Confidence-Set Conversion.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Leveraging Normalization Layer in Adapters with Progressive Learning and Adaptive Distillation for Cross-Domain Few-Shot Learning.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Accelerated MM Algorithms for Inference of Ranking Scores from Comparison Data.
Oper. Res., July, 2023

Test Score Algorithms for Budgeted Stochastic Utility Maximization.
INFORMS J. Optim., January, 2023

Improving Adaptability and Generalizability of Efficient Transfer Learning for Vision-Language Models.
CoRR, 2023

FedFN: Feature Normalization for Alleviating Data Heterogeneity Problem in Federated Learning.
CoRR, 2023

Carpe Diem: On the Evaluation of World Knowledge in Lifelong Language Models.
CoRR, 2023

Fine-Tuning the Retrieval Mechanism for Tabular Deep Learning.
CoRR, 2023

Distort, Distract, Decode: Instruction-Tuned Model Can Refine its Response from Noisy Instructions.
CoRR, 2023

Non-backtracking Graph Neural Networks.
CoRR, 2023

Cross-Modal Retrieval Meets Inference: Improving Zero-Shot Classification with Cross-Modal Retrieval.
CoRR, 2023

FedSoL: Bridging Global Alignment and Local Generality in Federated Learning.
CoRR, 2023

Instance-Optimal Cluster Recovery in the Labeled Stochastic Block Model.
CoRR, 2023

Enhancing Generalization and Plasticity for Sample Efficient Reinforcement Learning.
CoRR, 2023

Communication-Efficient Collaborative Heterogeneous Bandits in Networks.
CoRR, 2023

The StarCraft Multi-Agent Exploration Challenges: Learning Multi-Stage Tasks and Environmental Factors Without Precise Reward Functions.
IEEE Access, 2023

Meta-Learning Amidst Heterogeneity and Ambiguity.
IEEE Access, 2023

Flooding with Absorption: An Efficient Protocol for Heterogeneous Bandits over Complex Networks.
Proceedings of the 27th International Conference on Principles of Distributed Systems, 2023

Fair Streaming Principal Component Analysis: Statistical and Algorithmic Viewpoint.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

PLASTIC: Improving Input and Label Plasticity for Sample Efficient Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Recycle-and-Distill: Universal Compression Strategy for Transformer-based Speech SSL Models with Attention Map Reusing and Masking Distillation.
Proceedings of the 24th Annual Conference of the International Speech Communication Association, 2023

Patch-Mix Contrastive Learning with Audio Spectrogram Transformer on Respiratory Sound Classification.
Proceedings of the 24th Annual Conference of the International Speech Communication Association, 2023

Mitigating Dataset Bias by Using Per-Sample Gradient.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

CUDA: Curriculum of Data Augmentation for Long-tailed Recognition.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

HARE: Explainable Hate Speech Detection with Step-by-Step Reasoning.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Bayesian Multi-Task Transfer Learning for Soft Prompt Tuning.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

NASH: A Simple Unified Framework of Structured Pruning for Accelerating Encoder-Decoder Language Models.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Fast and Robust Early-Exiting Framework for Autoregressive Language Models with Synchronized Parallel Decoding.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Revisiting Intermediate Layer Distillation for Compressing Language Models: An Overfitting Perspective.
Proceedings of the Findings of the Association for Computational Linguistics: EACL 2023, 2023

Coreset Sampling from Open-Set for Fine-Grained Self-Supervised Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Re-Thinking Federated Active Learning Based on Inter-Class Diversity.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Toward Risk-based Optimistic Exploration for Cooperative Multi-Agent Reinforcement Learning.
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

Contextual Linear Bandits under Noisy Features: Towards Bayesian Oracles.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Nearly Optimal Latent State Decoding in Block MDPs.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Large Language Models Are Reasoning Teachers.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

A Gift from Label Smoothing: Robust Training with Adaptive Label Smoothing via Auxiliary Classifier under Label Noise.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Self-Contrastive Learning: Single-Viewed Supervised Contrastive Framework Using Sub-network.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Denoising after Entropy-Based Debiasing a Robust Training Method for Dataset Bias with Noisy Labels.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Region-Conditioned Orthogonal 3D U-Net for Weather4Cast Competition.
CoRR, 2022

The StarCraft Multi-Agent Challenges+ : Learning of Multi-Stage Tasks and Environmental Factors without Precise Reward Functions.
CoRR, 2022

Benchmark Dataset for Precipitation Forecasting by Post-Processing the Numerical Weather Prediction.
CoRR, 2022

Risk Perspective Exploration in Distributional Reinforcement Learning.
CoRR, 2022

Revisiting Architecture-aware Knowledge Distillation: Smaller Models and Faster Search.
CoRR, 2022

Demystifying the Base and Novel Performances for Few-shot Class-incremental Learning.
CoRR, 2022

ALASCA: Rethinking Label Smoothing for Deep Learning Under Label Noise.
CoRR, 2022

Supernet Training for Federated Image Classification under System Heterogeneity.
CoRR, 2022

Adversarial Bandits Robust to S-Switch Regret.
CoRR, 2022

Revisiting the Updates of a Pre-trained Model for Few-shot Learning.
CoRR, 2022

SuperNet in Neural Architecture Search: A Taxonomic Survey.
CoRR, 2022

Understanding Cross-Domain Few-Shot Learning: An Experimental Study.
CoRR, 2022

Mold into a Graph: Efficient Bayesian Optimization over Mixed-Spaces.
CoRR, 2022

Revisiting Orthogonality Regularization: A Study for Convolutional Neural Networks in Image Classification.
IEEE Access, 2022

Calibration of Few-Shot Classification Tasks: Mitigating Misconfidence From Distribution Mismatch.
IEEE Access, 2022

Understanding Cross-Domain Few-Shot Learning Based on Domain Similarity and Few-Shot Difficulty.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

MEDIAR: Harmony of Data-Centric and Model-Centric for Multi-Modality Microscopy.
Proceedings of The Cell Segmentation Challenge in Multi-modality High-Resolution Microscopy Images, 2022

Preservation of the Global Knowledge by Not-True Distillation in Federated Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Robust Streaming PCA.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Rotting Infinitely Many-Armed Bandits.
Proceedings of the International Conference on Machine Learning, 2022

Real-time and Explainable Detection of Epidemics with Global News Data.
Proceedings of the 1st Workshop on Healthcare AI and COVID-19, 2022

FedBABU: Toward Enhanced Representation for Federated Image Classification.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Neural Processes with Stochastic Attention: Paying more attention to the context dataset.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Synergy with Translation Artifacts for Training and Inference in Multilingual Tasks.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

ReFine: Re-randomization before Fine-tuning for Cross-domain Few-shot Learning.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

FedRN: Exploiting k-Reliable Neighbors Towards Robust Federated Learning.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021
A Test Score-Based Approach to Stochastic Submodular Optimization.
Manag. Sci., 2021

Meta-learning Amidst Heterogeneity and Ambiguity.
CoRR, 2021

Self-Contrastive Learning.
CoRR, 2021

FedBABU: Towards Enhanced Representation for Federated Image Classification.
CoRR, 2021

Preservation of the Global Knowledge by Not-True Self Knowledge Distillation in Federated Learning.
CoRR, 2021

FINE Samples for Learning with Noisy Labels.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021


Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge Distillation.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Improved Regret Bounds of Bilinear Bandits using Action Space Analysis.
Proceedings of the 38th International Conference on Machine Learning, 2021

BOIL: Towards Representation Change for Few-shot Learning.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Reinforcement with Fading Memories.
Math. Oper. Res., 2020

Adaptive Local Bayesian Optimization Over Multiple Discrete Variables.
CoRR, 2020

Accurate and Fast Federated Learning via Combinatorial Multi-Armed Bandits.
CoRR, 2020

TornadoAggregate: Accurate and Scalable Federated Learning via the Ring-Based Architecture.
CoRR, 2020

MixCo: Mix-up Contrastive Learning for Visual Representation.
CoRR, 2020

Does MAML really want feature reuse only?
CoRR, 2020

Regret in Online Recommendation Systems.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

SIPA: A Simple Framework for Efficient Networks.
Proceedings of the 20th International Conference on Data Mining Workshops, 2020

Precipitation Nowcasting Using Grid-based Data in South Korea Region.
Proceedings of the 20th International Conference on Data Mining Workshops, 2020

FEWER: Federated Weight Recovery.
Proceedings of the DistributedML@CoNEXT 2020: Proceedings of the 1st Workshop on Distributed Machine Learning, 2020

Accelerating Randomly Projected Gradient with Variance Reduction.
Proceedings of the 2020 IEEE International Conference on Big Data and Smart Computing, 2020

Convergence Rates of Gradient Descent and MM Algorithms for Bradley-Terry Models.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Non-Stationary Streaming PCA.
CoRR, 2019

Convergence Rates of Gradient Descent and MM Algorithms for Generalized Bradley-Terry Models.
CoRR, 2019

A pipelined hybrid recommender system for ranking the items on the display.
Proceedings of the Workshop on ACM Recommender Systems Challenge, 2019

Optimal Sampling and Clustering in the Stochastic Block Model.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Efficient Model for Image Classification With Regularization Tricks.
Proceedings of the NeurIPS 2019 Competition and Demonstration Track, 2019

Spectral Approximate Inference.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
Game Theoretic Perspective of Optimal CSMA.
IEEE Trans. Wirel. Commun., 2018

Spectrogram-channels u-net: a source separation model viewing each channel as the spectrogram of each source.
CoRR, 2018

Noisy Power Method with Grassmann Average.
Proceedings of the 2018 IEEE International Conference on Big Data and Smart Computing, 2018

2017
Clustering in Block Markov Chains.
CoRR, 2017

Contextual Multi-armed Bandits under Feature Uncertainty.
CoRR, 2017

On the Delay Scaling Laws of Cache Networks.
Proceedings of the 12th International Conference on Future Internet Technologies, 2017

Collaborative Clustering: Sample Complexity and Efficient Algorithms.
Proceedings of the International Conference on Algorithmic Learning Theory, 2017

2016
Distributed Medium Access Over Time-Varying Channels.
IEEE/ACM Trans. Netw., 2016

Delay Optimal CSMA With Linear Virtual Channels Under a General Topology.
IEEE/ACM Trans. Netw., 2016

Sketching with Test Scores and Submodular Maximization.
CoRR, 2016

Optimal Cluster Recovery in the Labeled Stochastic Block Model.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Distributed coordination maximization over networks: a stochastic approximation approach.
Proceedings of the 17th ACM International Symposium on Mobile Ad Hoc Networking and Computing, 2016

Parameter Estimation for Generalized Thurstone Choice Models.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
CSMA Using the Bethe Approximation: Scheduling and Utility Maximization.
IEEE Trans. Inf. Theory, 2015

Optimality of Spectral Algorithms for Community Detection in the Labeled Stochastic Block Model.
CoRR, 2015

Distributed Proportional Fair Load Balancing in Heterogenous Systems.
Proceedings of the 2015 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, 2015

Fast and Memory Optimal Low-Rank Matrix Approximation.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014
Accurate Community Detection in the Stochastic Block Model via Spectral Algorithms.
CoRR, 2014

Streaming, Memory Limited Algorithms for Community Detection.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Provable per-link delay-optimal CSMA for general wireless network topology.
Proceedings of the 2014 IEEE Conference on Computer Communications, 2014

Distributed learning for utility maximization over CSMA-based wireless multihop networks.
Proceedings of the 2014 IEEE Conference on Computer Communications, 2014

Community Detection via Random and Adaptive Sampling.
Proceedings of The 27th Conference on Learning Theory, 2014

Distributed load balancing in heterogenous systems.
Proceedings of the 48th Annual Conference on Information Sciences and Systems, 2014

2013
CSMA using Statistical Physics toward Throughput and Utility Optimal CSMA.
CoRR, 2013

CSMA over time-varying channels: optimality, uniqueness and limited backoff rate.
Proceedings of the Fourteenth ACM International Symposium on Mobile Ad Hoc Networking and Computing, 2013

CSMA using the Bethe approximation for utility maximization.
Proceedings of the 2013 IEEE International Symposium on Information Theory, 2013

2012
The Economic Effects of Sharing Femtocells.
IEEE J. Sel. Areas Commun., 2012

From Glauber dynamics to Metropolis algorithm: Smaller delay in optimal CSMA.
Proceedings of the 2012 IEEE International Symposium on Information Theory, 2012

Optimal CSMA: A survey.
Proceedings of the IEEE International Conference on Communication Systems, 2012

2011
Open or close: On the sharing of femtocells.
Proceedings of the INFOCOM 2011. 30th IEEE International Conference on Computer Communications, 2011

Multi-channel MAC protocol for QoS support in ad-hoc network.
Proceedings of the 2011 IEEE Consumer Communications and Networking Conference, 2011

2010
Traffic density based power control scheme for femto AP.
Proceedings of the IEEE 21st International Symposium on Personal, 2010

On the pricing of femtocell services.
Proceedings of the Conference on the Future of the Internet 2010, 2010

2009
Decentralized power control scheme in femtocell networks: A game theoretic approach.
Proceedings of the IEEE 20th International Symposium on Personal, 2009


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