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ICLR 2024 (International Conference on Learning Representations), Vien…

Accurate Retraining-free Pruning for Pretrained Encoder-based Language Models
Seungcheol Park, Hojun Choi, and U Kang # 강유 교수팀 

NeurIPS 2023 (신경정보처리시스템학회)

SHOT: Suppressing the Hessian along the Optimization Trajectory for Gradient-Based Meta-Learning (JunHoo Lee, Jayeon Yoo, Nojun Kwak) #곽노준 교수팀

ConcatPlexer : Additional Dim1 Batching for Faster ViTs (Donghoon Han, Seunghyeon Seo, Donghyeon Jeon, Jiho Jang, Chaerin Kong, Nojun Kwak) #곽노준 교수팀 

Recasting Continual Learning as Sequence Modeling (Soochan Lee, Jaehyeon Son and Gunhee Kim) #김건희 교수팀

Diversify & Conquer: Outcome-directed Curriculum RL via Out-of-Distribution Disagreement (Daesol Cho, Seungjae Lee, and H. Jin Kim) #김현진 교수팀 

CQM: Curriculum Reinforcement Learning with a Quantized World Model (Seungjae Lee, Daesol Cho, Jonghae Park, and H. Jin Kim) #김현진 교수팀 

Boosting Learning for LDPC Codes to Improve the Error-Floor Performance (Hee-Youl Kwak, Dae-Young Yun, Yongjune Kim, Sang-Hyo Kim, and Jong-Seon No) #노종선 교수팀 

SwiFT: Swin 4D fMRI Transformer (Peter Yongho Kim, Junbeom Kwon, Sunghwan Joo, Sangyoon Bae, Donggyu Lee, Yoonho Jung, Shinjae Yoo, Jiook Cha, and Taesup Moon) #문태섭 교수팀 

Energy-Based Models for Anomaly Detection: A Manifold Diffusion Recovery Approach (Sangwoong Yoon, Young-Uk Jin, Yung-Kyun Noh, and Frank C. Park) #박종우 교수팀 

Variational Weighting for Kernel Density Ratios (Sangwoong Yoon, Frank C. Park, Gunsu YUN, Iljung Kim, and Yung-Kyun Noh) #박종우 교수팀 

Direct Preference-based Policy Optimization without Reward Modeling (Gaon An*, Junhyeok Lee*, Xingdong Zuo, Norio Kosaka, Kyung-Min Kim, Hyun Oh Song) #송현오 교수팀 

Neural Relation Graph: A Unified Framework for Identifying Label Noise and Outlier Data (Jang-Hyun Kim, Sangdoo Yun, Hyun Oh Song) #송현오 교수팀 

Discovering Hierarchical Achievements in Reinforcement Learning via Contrastive Learning (Seungyong Moon, Junyoung Yeom, Bumsoo Park, Hyun Oh Song) #송현오 교수팀 

ProPILE: Probing Privacy Leakage in Large Language Models (Siwon Kim, Sangdoo Yun, Hwaran Lee, Martin Gubri, Sungroh Yoon, Seong Joon Oh) #윤성로 교수팀 

PUCA: Patch-Unshuffle and Channel Attention for Enhanced Self-Supervised Image Denoising (Hyemi Jang, Junsung Park, Dahuin Jung, Jaihyun Lew, Ho Bae, Sungroh Yoon) #윤성로 교수팀 

On the Powerfulness of Textual Outliers for Visual OoD Detection (Sangha Park, Jisoo Mok, Dahuin Jung, Saehyung Lee, Sungroh Yoon) #윤성로 교수팀 

CLeAR: Continual Learning on Algorithmic Reasoning for Human-like Intelligence (Bong Gyun Kang, HyunGi Kim, Dahuin Jung, Sungroh Yoon) #윤성로 교수팀 

P-Flow: A Fast and Data-Efficient Zero-Shot TTS through Speech Prompting (Sungwon Kim, Kevin J. Shih, Rohan Badlani, Joao Felipe Santos, Evelina Bakhturina, Mikyas T. Desta, Rafael Valle, Sungroh Yoon, Bryan Catanzaro) #윤성로 교수팀 

Conditional Score Guidance for Text-Driven Image-to-Image Translation (Hyunsoo Lee*, Minsoo Kang*, and Bohyung Han) #한보형 교수팀 

Generative Neural Fields by Mixtures of Neural Implicit Functions (Tackgeun You, Jungtaek Kim, Mijeong Kim, and Bohyung Han) #한보형 교수팀 

Beyond Pretrained Features: Noisy Image Modeling Provides Adversarial Defense (Zunzhi You, Daochang Liu, Bohyung Han, and Chang Xu) #한보형 교수팀 

SPQR: Controlling Q-ensemble Independence for Reinforcement Learning (Dohyeok Lee, Seungyub Han, Taehyun Cho, and Jungwoo Lee) #이정우 교수팀 

Pitfall of Optimism: Distributional Reinforcement Learning by Randomizing Risk Criterion (Taehyun Cho, Seungyub Han, Heesoo Lee, Kyungjae Lee, and Jungwoo Lee) #이정우 교수팀 

MEMTO: Memory-guided Transformer for Multivariate Time Series Anomaly Detection (Junho Song, Keonwoo Kim, Jeonglyul Oh, Sungzoon Cho) #조성준 교수팀

ICML 2023 (국제머신러닝학회)

(poster) End-to-End Multi-Object Detection with a Regularized Mixture Model (Jaeyoung Yoo · Hojun Lee · Seunghyeon Seo · Inseop Chung · NOJUN KWAK) #곽노준 교수팀 

(poster) Accelerated Infeasibility Detection of Constrained Optimization and Fixed-Point Iterations (Jisun Park, Ernest Ryu) #류경석 교수팀 

(poster) Rotation and Translation Invariant Representation Learning with Implicit Neural Representations (Sehyun Kwon, Joo Young Choi, Ernest Ryu) #류경석 교수팀 

(poster) Long-Tailed Recognition by Mutual Information Maximization between Latent Features and Ground-Truth Labels (Min-Kook Suh, Seung-Woo Seo) #서승우 교수팀 

(poster) Unsupervised Skill Discovery for Learning Shared Structures across Changing Environments (Sang-Hyun Lee, Seung-Woo Seo) #서승우 교수팀 

(poster) Efficient Latency-Aware CNN Depth Compression via Two-Stage Dynamic Programming (Jinuk Kim, Yeonwoo Jeong, Deokjae Lee, Hyun Oh Song) #송현오 교수팀 

(poster) Improving Visual Prompt Tuning for Self-supervised Vision Transformers (Seungryong Yoo, Eunji Kim, Dahuin Jung, JUNGBEOM LEE, Sungroh Yoon) #윤성로 교수팀 

(poster) Probabilistic Concept Bottleneck Models (Eunji Kim, Dahuin Jung, Sangha Park, Siwon Kim, Sungroh Yoon) #윤성로 교수팀 

(poster) On the Impact of Knowledge Distillation for Model Interpretability (Hyeongrok Han, Siwon Kim, Hyun-Soo Choi, Sungroh Yoon) #윤성로 교수팀 

(poster) Implicit Jacobian regularization weighted with impurity of probability output ( Sungyoon Lee · Jinseong Park · Jaewook Lee) #이재욱 교수팀

(poster) Differentially Private Sharpness-Aware Training (Jinseong Park, Hoki Kim, Yujin Choi, Jaewook Lee) #이재욱 교수팀 

(poster) BPipe: Memory-Balanced Pipeline Parallelism for Training Large Language Models (Taebum Kim, Hyoungjoo Kim, Gyeong-In Yu, Byung-Gon Chun) #전병곤 교수팀

Combinatorial Neural Bandits (Taehyun Hwang, Kyuwook Chai, Min-hwan Oh) #오민환 교수팀 

Model-based Offline Reinforcement Learning with Count-based Conservatism (Byeongchan Kim, Min-hwan Oh) #오민환 교수팀

Semi-Parametric Contextual Pricing Algorithm using Cox Proportional Hazards Model (Young-Geun Choi, Gi-Soo Kim, Yunseo Choi, Wooseong Cho, Myunghee Cho Paik, Min-hwan Oh) #오민환 교수, 조명희 교수팀

ICLR 2023 (표현 학습 국제학회)

Recursion of Thought: Divide and Conquer Reasoning with Language Models (Soochan Lee, Gunhee Kim) #김건희 교수팀 

HyPHEN: A Hybrid Packing Method and Optimizations for Homomorphic Encryption-Based Neural Network (Jaiyoung Park, Donghwan Kim, Jung Ho Ahn) #안정호 교수팀 

SDAC: Efficient Safe Reinforcement Learning with Low-Biased Distributional Actor-Critic (Dohyeong Kim, Kyungjae Lee, Songhwai Oh) #오성회 교수팀 

Wasserstein Fair Autoencoders (Sungdong Lee, Hyunjong Lee, Joong-Ho Won) #원중호 교수팀 

AdaStride: Using Adaptive Strides in Sequential Data for Effective Downsampling (Yoonhyung Lee, Kyomin Jung) #정교민 교수팀 

Revisiting Group Robustness: Class-specific Scaling is All You Need (Seonguk Seo, Bohyung Han) #한보형 교수팀 

Communication-Efficient Federated Learning with Accelerated Client Gradient (Geeho Kim, Jinkyu Kim, Bohyung Han) #한보형 교수팀 

(poster) DepthFL : Depthwise Federated Learning for Heterogeneous Clients (Minjae Kim, Sangyoon Yu, Suhyun Kim, Soo-Mook Moon) #문수묵 교수팀 

(poster)Re-weighting Based Group Fairness Regularization via Classwise Robust Optimization (Sangwon Jung, Taeeon Park, Sanghyuk Chun, Taesup Moon) #문태섭 교수팀 

(poster) Geometrically regularized autoencoders for non-Euclidean data (Cheongjae Jang, Yonghyeon Lee, Yung-Kyun Noh, Frank C. Park) #박종우 교수팀 

(poster) New Insights for the Stability-Plasticity Dilemma in Online Continual Learning (Dahuin Jung, Dongjin Lee, Sunwon Hong, Hyemi Jang, Ho Bae, Sungroh Yoon) #윤성로 교수팀 

(poster) BigVGAN: A Universal Neural Vocoder with Large-Scale Training (Sang-gil Lee, Wei Ping, Boris Ginsburg, Bryan Catanzaro, Sungroh Yoon) #윤성로 교수팀 

(poster) Learning with Auxiliary Activation for Memory-Efficient Training (Sunghyeon Woo, Dongsuk Jeon) #전동석 교수팀 

(poster) Confidence-Based Feature Imputation for Graphs with Partially Known Features (Daeho Um, Jiwoong Park, Seulki Park, Jin young Choi) #최진영 교수팀 

AAAI 2023 (국제인공지능학회)

Unifying Vision-Language Representation Space with Single-tower Transformer (Jiho Jang, Chaerin Kong, DongHyeon Jeon, Seonhoon Kim, Nojun Kwak) #곽노준 교수팀 

Towards More Robust Interpretation via Local Gradient Alignment (Sunghwan Joo, SeokHyeon Jeong, Juyeon Heo, Adrian Weller, and Taesup Moon) #문태섭 교수팀 

Prompt-Augmented Linear Probing: Scaling Beyond The Limit of Few-shot In-Context Learners (Hyunsoo Cho, Hyuhng Joon Kim, Jun Yeob Kim, Sang-Woo Lee, Sang-goo Lee, Kang Min Yoo, Taeuk Kim) #이상구 교수팀 

Not All Neighbors Matter: Point Distribution-Aware Pruning for 3D Point Cloud (Yejin Lee, Donghyun Lee, JungUk Hong, Jae W. Lee, and Hongil Yoon) #이재욱 교수팀 

Overcoming Three Discrepancies for Low-Resource Language Specialization (Jaeseong Lee, Dohyeon Lee, Seung-won Hwang) #황승원 교수팀 

Long-Term 3D Human Motion Generation from Multiple Action Labels (Taeryung Lee, Gyeongsik Moon, Kyoung Mu Lee) #이경무 교수팀 

Diversified and Realistic 3D Augmentation via Iterative Construction, Random Placement, and HPR Occlusion (Jungwook Shin, Jaeill Kim, Kyungeun Lee, Hyunghun Cho, Wonjong Rhee) #이원종 교수팀

Model-based Reinforcement Learning with Multinomial Logistic Function Approximation (Taehyun Hwang, Min-hwan Oh) #오민환 교수팀

NeurIPS 2022 (신경정보처리시스템학회)

Robust Imitation via Mirror Descent Inverse Reinforcement Learning (D.-S.Han, H.-S.Kim, H.-D.Lee, J.-H.Ryu, B.-T.Zhang) #장병탁 교수팀

SelecMix: Debiased Learning by Contradicting-pair Sampling (Inwoo Hwang · Sangjun Lee · Yunhyeok Kwak · Seong Joon Oh · Damien Teney · Jin-Hwa Kim · Byoung-Tak Zhang) #장병탁 교수팀 

S2P: State-conditioned Image Synthesis for Data Augmentation in Offline Reinforcement Learning (Daesol Cho · Dongseok Shim · H. Jin Kim) #김현진 교수팀 

DHRL: A Graph-Based Approach for Long-Horizon and Sparse Hierarchical Reinforcement Learning (Seungjae Lee · Jigang Kim · Inkyu Jang · H. Jin Kim) #김현진 교수팀 

MCL-GAN: Generative Adversarial Networks with Multiple Specialized Discriminators (Jinyoung Choi · Bohyung Han) #한보형 교수팀 

Locally Hierarchical Auto-Regressive Modeling for Image Generation (Tackgeun You · Saehoon Kim · Chiheon Kim · Doyup Lee · Bohyung Han) #한보형 교수팀 

Information-Theoretic Generative Model Compression with Variational Energy-based Model (Minsoo Kang · Hyewon Yoo · Eunhee Kang · Sehwan Ki · Hyong Euk Lee · Bohyung Han) #한보형 교수팀 

Rethinking Value Function Learning for Generalization in Reinforcement Learning (Seungyong Moon · JunYeong Lee · Hyun Oh Song) #송현오 교수팀 

Descent Steps of a Relation-Aware Energy Produce Heterogeneous Graph Neural Networks (Hongjoon Ahn · Yongyi Yang · Quan Gan · David P Wipf · Taesup Moon) #문태섭 교수팀 

Constrained GPI for Zero-Shot Transfer in Reinforcement Learning (Jaekyeom Kim · Seohong Park · Gunhee Kim) #김건희 교수팀

ICML 2022 (국제머신러닝학회)

AutoSNN: Towards Energy-Efficient Spiking Neural Networks (Byunggook Na, Jisoo Mok, Seongsik Park, Dongjin Lee, Hyeokjun Choe, Sungroh Yoon) #윤성로 교수팀

Guided-TTS: A Diffusion Model for Text-to-Speech via Classifier Guidance (Heeseung Kim, Sungwon Kim, Sungroh Yoon) #윤성로 교수팀

Confidence Score for Source-Free Unsupervised Domain Adaptation (Jonghyun Lee, Dahuin Jung, Junho Yim, Sungroh Yoon) #윤성로 교수팀

Dataset Condensation with Contrastive Signals (Saehyung Lee, SANGHYUK CHUN, Sangwon Jung, Sangdoo Yun, Sungroh Yoon) #윤성로 교수팀

Neural Tangent Kernel Analysis of Deep Narrow Neural Networks (Jongmin Lee, Joo Young Choi, Ernest Ryu, Albert No) #류경석 교수팀

(Long) Exact Optimal Accelerated Complexity for Fixed-Point Iterations (Jisun Park, Ernest Ryu) #류경석 교수팀

(Long) Continuous-Time Analysis of Accelerated Gradient Methods via Conservation Laws in Dilated Coordinate Systems (Jaewook Suh, Gyumin Roh, Ernest Ryu) #류경석 교수팀

Multi-Level Branched Regularization for Federated Learning (Jinkyu Kim, Geeho Kim, Bohyung Han) #한보형 교수팀

Information-Intensive Dataset Condensation (Jang-Hyun Kim, Jinuk Kim, Seong Joon Oh, Sangdoo Yun, Hwanjun Song, Joonhyun Jeong, Jung-Woo Ha, Hyun Oh Song) #송현오 교수팀

Query-Efficient and Scalable Black-Box Adversarial Attacks on Discrete Sequential Data via Bayesian Optimization (Deokjae Lee, Seungyong Moon, Junhyeok Lee, Hyun Oh Song) #송현오 교수팀

Variational On-the-Fly Personalization (Kim Jangho, Jun-Tae Lee, Simyung Chang, NOJUN KWAK) #곽노준 교수팀

Statistical inference with implicit SGD: proximal Robbins-Monro vs. Polyak-Ruppert (Yoonhyung Lee, Sungdong Lee, Joong-Ho (Johann) Won) #원중호 교수팀

A Statistical Manifold Framework for Point Cloud Data (Yonghyeon Lee, Seungyeon Kim, Jinwon Choi, Frank Chongwoo Park) #박종우 교수팀

Learning fair representation with a parametric integral probability metric (Dongha Kim, Kunwoong Kim, InSung Kong, Ilsang Ohn, Yongdai Kim) #김용대 교수팀

Accelerated Gradient Methods for Geodesically Convex Optimization: Tractable Algorithms and Convergence Analysis (Jungbin Kim, Insoon Yang) #양인순 교수팀

Low-Complexity Deep Convolutional Neural Networks on Fully Homomorphic Encryption Using Multiplexed Parallel Convolutions (Eunsang Lee · Joon-Woo Lee · Junghyun Lee · Young-Sik KIM (Chosun University) · Yongjune Kim (DGIST) · Jong-Seon No · Woosuk Choi (Samsung)) #노종선 교수팀

Counterfactual Transportability: A Formal Approach (Juan Correa (Universidad Autónoma de Manizales) · Sanghack Lee · Elias Bareinboim (Columbia)) #이상학 교수팀

ICLR 2022 (표현 학습 국제학회)

Lipschitz-constrained Unsupervised Skill Discovery (Seohong Park, Jongwook Choi, Jaekyeom Kim, Honglak Lee and Gunhee Kim) #김건희 교수팀

Neural Variational Dropout Processes (Insu Jeon, Youngjin Park and Gunhee Kim) #김건희 교수팀

Regularized Autoencoders for Isometric Representation Learning (Yonghyeon Lee, Sangwoong Yoon, Minjun Son, Frank C. Park) #박종우 교수팀 

PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Prior (Sang-gil Lee, Heeseung Kim, Chaehun Shin, Xu Tan, Chang Liu, Qi Meng, Tao Qin, Wei Chen, Sungroh Yoon, Tie-Yan Liu) #윤성로 교수팀 

Stein Latent Optimization for Generative Adversarial Networks (Uiwon Hwang, Heeseung Kim, Dahuin Jung, Hyemi Jang, Hyungyu Lee, Sungroh Yoon) #윤성로 교수팀 

Toward Efficient Low-Precision Training: Data Format Optimization and Hysteresis Quantization (Sunwoo Lee, Jeongwoo Park, Dongsuk Jeon) #전동석 교수팀 

SUMNAS: Supernet with Unbiased Meta-Features for Neural Architecture Search (Hyeonmin Ha, Ji-Hoon Kim, Semin Park, Byung-Gon Chun) #전병곤 교수팀 

AAAI 2022 (국제인공지능학회)

(Poster) Sparse Structure Learning via Graph Neural Networks for Inductive Document Classification (Yinhua Piao, Sangseon Lee, Dohoon Lee, Sun Kim) #김선 교수팀 

Preemptive Image Robustification for Protecting Users against Man-in-the-Middle Adversarial Attacks (Seungyong Moon, Gaon An, Hyun Oh Song) #송현오 교수팀 

Texture Generation Using Dual-Domain Feature Flow with Multi-View Hallucinations (Seunggyu Chang, Jungchan Cho, Songhwai Oh) #오송회 교수팀 

Towards a Rigorous Evaluation of Time-series Anomaly Detection (Siwon Kim, Kukjin Choi, Hyun-Soo Choi, Byunghan Lee, Sungroh Yoon) #윤성로 교수팀

VECA: A New Benchmark and Toolkit for General Cognitive Development (Kwanyoung Park, Hyunseok Oh, Youngki Lee) #이영기 교수팀 

Information-theoretic Bias Reduction via Causal View of Spurious Correlation (Seonguk Seo, Joon-Young Lee, Bohyung Han) #한보형 교수팀 

C2L: Causally Contrastive Learning for Robust Text Classification (Seungtaek Choi, Myeongho Jeong, Hojae Han, Seung-won Hwang) #황승원 교수팀 

Dual Task Framework for Improving Persona-grounded Dialogue Dataset (Minju Kim, Beong-woo Kwak, Youngwook Kim, Hong-in Lee, Seung-won Hwang, Jinyoung Yeo) #황승원 교수팀 

TrustAL: Trustworthy Active Learning using Knowledge Distillation (Beong-woo Kwak, Youngwook Kim, Yu Jin Kim, Seung-won Hwang, Jinyoung Yeo) #황승원 교수팀

NeurIPS 2021 (신경정보처리시스템학회)

Time Discretization-Invariant Safe Action Repetition for Policy Gradient Methods (Seohong Park, Jaekyeom Kim and Gunhee Kim) #김건희 교수팀

A Geometric Structure of Acceleration and Its Role in Making Gradients Small Fast (J. Lee, C. Park, E. K. Ryu) #류경석 교수팀

SSUL: Semantic Segmentation with Unknown Label for Exemplar-based Class-Incremental Learning (Sungmin Cha, Beomyoung Kim, Youngjoon Yoo, and Taesup Moon) #문태섭 교수팀

Neighborhood Reconstructing Autoencoders (Yonghyeon Lee, Hyeokjun Kwon, Frank Park) #박종우 교수팀

Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble (Gaon An, Seungyong Moon, Jang-Hyun Kim, Hyun Oh Song) #송현오 교수팀

Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (Jungbeom Lee, Jooyoung Choi, Jisoo Mok, Sungroh Yoon) #윤성로 교수팀

Neural Analysis and Synthesis: Reconstructing Speech from Self-Supervised Representations (Hyeong-Seok Choi, Juheon Lee, Wansoo Kim, Jie Hwan Lee, Hoon Heo, Kyogu Lee) #이교구 교수팀

Towards Better Understanding of Training Certifiably Robust Models against Adversarial Examples (Sungyoon Lee, Woojin Lee, Jinseong Park, Jaewook Lee) #이재욱 교수팀

Parameter-free HE-friendly Logistic Regression (Junyoung Byun, Woojin Lee,  Jaewook Lee) #이재욱 교수팀

Goal-Aware Cross-Entropy for Multi-Target Reinforcement Learning (Kibeom Kim, Min Whoo Lee, Yoonsung Kim, JeHwan Ryu, Minsu Lee, Byoung-Tak Zhang) #장병탁 교수팀

Activation Sharing with Asymmetric Paths Solves Weight Transport Problem without Bidirectional Connection (S. Woo, J. Park, J. Hong, and D. Jeon) #전동석 교수팀

Terra: Imperative-Symbolic Co-Execution of Imperative Deep Learning Parograms (Taebum Kim, Eunji Jeong, Geon-Woo Kim, Yunmo Koo, Sehoon Kim, Gyeong-In Yu, Byung-Gon Chun) #전병곤 교수팀 

Doubly Robust Thompson Sampling with Linear Payoffs (Wonyoung Kim, Gi-Soo Kim, Myunghee Cho Paik) #조명희 교수팀

Learning Student-Friendly Teacher Networks for Knowledge Distillation (Dae Young Park, Moon-Hyun Cha, Changwook Jeong, Daesin Kim, and Bohyung Han) #한보형 교수팀

Learning Debiased and Disentangled Representations for Semantic Segmentation (Sanghyeok Chu, Dongwan Kim, and Bohyung Han) #한보형 교수팀

SWAD: Domain Generalization by Seeking Flat Minima (Junbum Cha (Kakao Brain) · Sanghyuk Chun (NAVER AI Lab) · Kyungjae Lee (서울대학교) · Han-Cheol Cho (Intel Korea) · Seunghyun Park (Clova AI Research, Naver Corp.) · Yunsung Lee (Korea University) · Sungrae Park (UPSTAGE))

Neural Bootstrapper (Minsuk Shin (University of South Carolina) · Hyungjoo Cho (서울대학교) · Hyun-seok Min (Tomocube) · Sungbin Lim (UNIST))

MERLOT: Multimodal Neural Script Knowledge Models (Rowan Zellers (University of Washington) · Ximing Lu (Department of Computer Science, University of Washington) · Jack Hessel (Cornell University) · Youngjae Yu (서울대학교) · Jae Sung Park (University of Washington) · Jize Cao (Department of Computer Science, University of Washington) · Ali Farhadi (University of Washington, Allen Institute for Artificial Intelligence) · Yejin Choi (University of Washington)) 

ICML 2021 (국제머신러닝학회)

(Long Talk) Unsupervised Representation Learning via Neural Activation Coding (Yookoon Park, Sangho Lee, Gunhee Kim and David Blei) #김건희 교수팀

(Long Talk) Accelerated Algorithms for Smooth Convex-Concave Minimax Problems with O(1/k^2) Rate on Squared Gradient Norm (TaeHo Yoon, Ernest Ryu) #류경석 교수팀

Unsupervised Skill Discovery with Bottleneck Option Learning (Jaekyeom Kim, Seohong Park and Gunhee Kim) #김건희 교수팀

WGAN with an Infinitely Wide Generator Has No Spurious Stationary Points (Albert No, TaeHo Yoon, Kwon Sehyun, Ernest Ryu) #류경석 교수팀

Autoencoding Under Normalization Constraints (Sangwoong Yoon, Yung-Kyun Noh, Frank Chongwoo Park) #박종우 교수팀

Sparsity-Agnostic Lasso Bandit (Min-hwan Oh, Garud Iyengar, Assaf Zeevi) #오민환 교수

Chebyshev Polynomial Codes: Task Entanglement-based Coding for Distributed Matrix Multiplication (Sangwoo Hong, Heecheol Yang, Youngseok Yoon, Taehyun Cho, and Jungwoo Lee) #이정우 교수팀

Learning from Nested Data with Ornstein Auto-Encoders (Youngwon Choi, Sungdong Lee, Joong-Ho Won) #원중호 교수팀

Message Passing Adaptive Resonance Theory for Online Active Semi-supervised Learning (Taehyeong Kim, Injune Hwang, Hyundo Lee, Hyunseo Kim, Won-Seok Choi, Joseph J. Lim, and Byoung-Tak Zhang) #장병탁 교수팀

AAAI 2021 (국제인공지능학회)

Self-supervised pre-training and contrastive representation learning for multiple-choice video QA (Seonhoon Kim, Seohyeong Jeong, Eunbyul Kim, Inho Kang, Nojun Kwak) #곽노준 교수팀

Dual Compositional Learning in Interactive Image Retrieval (Jongseok Kim, Youngjae Yu, Hoeseong Kim, Gunhee Kim) #김건희 교수팀

IB-GAN: Disengangled Representation Learning with Information Bottleneck Generative Adversarial Networks (Insu Jeon, Wonkwang Lee, Myeongjang Pyeon and Gunhee Kim) #김건희 교수팀

Understanding Catastrophic Overfitting in Single-Step Adversarial Training (Hoki Kim, Woojin Lee, Jaewook Lee) #이재욱 교수팀

DramaQA: Character-Centered Video Story Understanding with Hierarchical QA (Seongho Choi, Kyoung-Woon On, Yu-Jung Heo, Ahjeong Seo, Youwon Jang, Minsu Lee, Byoung-Tak Zhang) #장병탁 교수팀

Kernel-Convoluted Deep Neural Networks with Data Augmentation (Minjin Kim, Young-geun Kim, Dongha Kim, Yongdai Kim, Myunghee Cho Paik) #조명희 교수팀

Neural Sequence-to-grid Module for Learning Symbolic Rules (Segwang Kim, Hyoungwook Nam, Joonyoung Kim, and Kyomin Jung) #정교민 교수팀

Class-Attentive Diffusion Network for Semi-Supervised Classification (Jongin Lim, Daeho Um, Hyung Jin Chang, Dae Ung Jo, Jin Young Choi) #최진영 교수팀

AutoLR: Layer-wise Pruning and Auto-tuning of Learning Rates in Fine-tuning of Deep Networks (Youngmin Ro, Jin Young Choi) #최진영 교수팀

Image-to-Image Retrieval by Learning Similarity between Scene Graphs (Sangwoong Yoon, Woo Young Kang, Sungwook Jeon, SeongEun Lee, Changjin Han, Jonghun Park, Eun-Sol Kim) #박종헌 교수팀

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ICLR 2021 (표현 학습 국제학회)

(Oral) Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity (JangHyun Kim, Wonho Choo, Hosan Jeong, Hyun Oh Song) #송현오 교수팀

Parameter Efficient Multimodal Transformers for Video Representation Learning (Sangho Lee, Youngjae Yu, Gunhee Kim, Thomas Breuel, Jan Kautz, Yale Song) #김건희 교수팀

Self-Supervised Learning of Compressed Video Representations (Youngjae Yu, Sangho Lee, Gunhee Kim, Yale Song) #김건희 교수팀

SEDONA: Search for Decoupled Neural Networks toward Greedy Block-wise Learning (Myeongjang Pyeon, Jihwan Moon, Taeyoung Hahn, Gunhee Kim) #김건희 교수팀

Drop-Bottleneck: Learning Discrete Compressed Representation for Noise-Robust Exploration (Jaekyeom Kim, Minjung Kim, Dongyeon Woo, Gunhee Kim) #김건희 교수팀

GAN2GAN: Generative noise learning for blind image denoising with single noisy images (Sungmin Cha, Taeeon Park, Byeongjoon Kim, Jongduk Baek, and Taesup Moon) #문태섭 교수팀

CPR: Classifier-projection regularization for continual learning (Sungmin Cha, Hsiang Hsu, Taebaek Hwang, Flavio P. Calmon, and Taesup Moon) #문태섭 교수팀

Removing Undesirable Feature Contributions Using Out-of-Distribution Data (Saehyung Lee, Changhwa Park, Hyungyu Lee, Jihun Yi, Jonghyun Lee, Sungroh Yoon) #윤성로 교수팀

Bidirectional Variational Inference for Non-Autoregressive Text-to-Speech (Yoonhyung Lee, Joongbo Shin, Kyomin Jung) #정교민 교수팀

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IJCAI 2021 (인공 지능에 관한 국제공동회의)

Accelerating Neural Architecture Search via Proxy Data (Byunggook Na, Jisoo Mok, Hyeokjun Choe, Sungroh Yoon) #윤성로 교수팀

Masked Contrastive Learning for Anomaly Detection (Hyunsoo Cho, Jinseok Seol, Sang-goo Lee) #이상구 교수팀

ICTC 2020

Low-Rank Matrix Completion Using Graph Neural Network (Luong Trung Nguyen, Byonghyo Shim) #심병효 교수팀