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Selected Conference Publications on Machine Learning
- Stochastic Chebyshev Gradient Descent for Spectral Optimization (poster, video)
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 (poster, code, video)
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, video)
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, video)
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
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