Selected Conference Publications on Machine Learning

Stochastic Chebyshev Gradient Descent for Spectral Optimization

Insu Han, Haim Avron and Jinwoo Shin
Neural Information Processing Systems (NIPS) 2018
Spotlight Presentation (168/4856=3.5%)

A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks

Kimin Lee, Kibok Lee, Honglak Lee and Jinwoo Shin
Neural Information Processing Systems (NIPS) 2018
Spotlight Presentation (168/4856=3.5%)

Learning to Specialize with Knowledge Distillation for Visual Question Answering

Jonghwan Mun, Kimin Lee, Jinwoo Shin and Bohyung Han
Neural Information Processing Systems (NIPS) 2018

Neural Adaptive Content-aware Internet Video Delivery

Hyunho Yeo, Youngmok Jung, Jaehong Kim, Jinwoo Shin and Dongsu Han
The USENIX Symposium on Operating Systems Design and Implementation (OSDI) 2018

Bucket Renormalization for Approximate Inference (slide, poster)

Sungsoo Ahn, Michael Chertkov, Adrian Weller and Jinwoo Shin
International Conference on Machine Learning (ICML) 2018

Hierarchical Novelty Detection for Visual Object Recognition (poster, code)

Kibok Lee, Kimin Lee, Kyle Min, Yuting Zhang, Jinwoo Shin and Honglak Lee
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2018

Training Confidence-Calibrated Classifiers for Detecting Out-of-Distribution Samples (slide, poster, code)

Kimin Lee, Honglak Lee, Kibok Lee and Jinwoo Shin
International Conference on Learning Representations (ICLR) 2018

Gauged Mini-Bucket Elimination for Approximate Inference (poster)

Sungsoo Ahn, Michael Chertkov, Jinwoo Shin and Adrian Weller
International Conference on Artificial Intelligence and Statistics (AISTATS) 2018

Multi-armed Bandit with Additional Observations

Donggyu Yun, Sumyeong Ahn, Alexandre Proutiere, Jinwoo Shin and Yung Yi
ACM International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS) 2018

Gauging Variational Inference (slide, poster)

Sungsoo Ahn, Michael Chertkov and Jinwoo Shin
Neural Information Processing Systems (NIPS) 2017

Faster Greedy MAP Inference for Determinantal Point Processes (code)

Insu Han, Prabhanjan Kambadur, Kyoungsoo Park and Jinwoo Shin
International Conference on Machine Learning (ICML) 2017

Confident Multiple Choice Learning (slide, poster, code)

Kimin Lee, Changho Hwang, Kyoungsoo Park and Jinwoo Shin
International Conference on Machine Learning (ICML) 2017

Rapid Mixing Swendsen-Wang Sampler for Stochastic Partitioned Attractive Models (poster)

Sejun Park, Yunhun Jang andreas Galanis, Jinwoo Shin, Daniel Stefankovic and Eric Vigoda
International Conference on Artificial Intelligence and Statistics (AISTATS) 2017

Synthesis of MCMC and Belief Propagation (code)

Sungsoo Ahn, Michael Chertkov and Jinwoo Shin
Neural Information Processing Systems (NIPS) 2016
Full Oral Presentation (46/2500=1.8%)

Optimal Inference in Crowdsourced Classification via Belief Propagation

Jungseul Ok, Sewoong Oh, Jinwoo Shin and Yung Yi
International Conference on Machine Learning (ICML) 2016

Minimum Weight Perfect Matching via Blossom Belief Propagation

Sungsoo Ahn, Sejun Park, Michael Chertkov and Jinwoo Shin
Neural Information Processing Systems (NIPS) 2015
Spotlight Presentation (82/1838=4.5%)

Large-scale Log-determinant Computation through Stochastic Chebyshev Expansions (code)

Insu Han, Dmitry Malioutov and Jinwoo Shin
International Conference on Machine Learning (ICML) 2015

Max-Product Belief Propagation for Linear Programming: Applications to Combinatorial Optimization

Sejun Park and Jinwoo Shin
Conference on Uncertainty in Artificial Intelligence (UAI) 2015

A Graphical Transformation for Belief Propagation: Maximum Weight Matchings and Odd-Sized Cycles

Jinwoo Shin, Andrew E. Gelfand and Michael Chertkov
Neural Information Processing Systems (NIPS) 2013

The Complexity of Approximating a Bethe Equilibrium

Jinwoo Shin
International Conference on Artificial Intelligence and Statistics (AISTATS) 2012