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Hsiao-Yu Fish Tung

Machine Learning Department

Carnegie Mellon University

mail: htung at cs.cmu.edu

About me

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I am a second-year PhD student in the Machine Learning Department at CMU. I work with Professor Katerina Fragkiadaki on solving computer vision problem with virtual imaginations using deep learning, computational geometry and data-driven knowledge priors. My research goal is to teach machine to see, learn and think like humans.

I received my M.S. in CMU MLD and my B.S. in Electrical Engineering from National Taiwan University in 2013. During my master, I worked with Professor Alex Smola on spectral method for Bayesian models and succefully designed efficient and provable algorithms. In my undergraduate, I was one of the member in Professor Chih-Jen Lin 's team "Algorithm @ National Taiwan University" and won the KDD CUP 2013 Championship on both Track1 and Track2.

Preprint

Spectral Methods for Nonparametric Models [Paper]

Hsiao-Yu Fish Tung, Chao-Yuan Wu, Manzil Zaheer, Alexander J. Smola

Conference Papers

Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy [Paper]

Dougal J. Sutherland, Hsiao-Yu Tung, Heiko Strathmann, Soumyajit De, Aaditya Ramdas, Alexander J. Smola, Arthur Gretton
International Conference on Learning Representations, ICLR 2017.

Fast and Guaranteed Tensor Decomposition via Sketching [Paper]

Yining Wang, Hsiao-Yu Tung, Alexander J. Smola, Animashree Anandkumar
Neural Information Processing Systems, NIPS 2015, spotlight.

Spectral Methods for Indian Buffet Process Inference. [Paper]

Hsiao-Yu F. Tung, Alexander J. Smola
Neural Information Processing Systems, NIPS 2014.

Novel Traffic Light Timing Adjustment Strategy Based On Genetic Algorithm. [Paper]

Hsiao-Yu Tung, Wei-Chiu Ma, and Tian-Li Yu
IEEE Congress on Evolutionary Computation, IEEE CEC 2013, Oral.

Effective String Processing and Matching for Author Disambiguation. [Paper]

W.-S. Chin, Y.-C. Juan, Y.-Zhuang, Felix Wu, H.-Y. Tung, T. Yu, J.-P. Wang, C.-X. Chang, C.-P. Yang, W.-C. Chang, K.-H. Huang, T.-M. Kuo, S.-W. Lin, Y.-S. Lin, Y.-C. Lu, Y.-C. Su, C.-K. Wei, T.- C. Yin, C.-L. Li, T.-W. Lin, C.-H. Tsai, S.-d. Lin, H.-T. Lin, C.-J. Lin
KDD Cup 2013 Workshop, KDD 2013

Combination of Feature Engineering and Ranking Models for Paper-Author Identification in KDD Cup 2013 [Paper]

C.-L. Li, Y.-C. Su, T.-W. Lin, C.-H. Tsai, W.-C. Chang, K.-H. Huang, T.-M. Kuo, S.-W. Lin, Y.-S. Lin, Y.-C. Lu, C.-P. Yang, C.-X. Chang, W.-S. Chin, Y.-C. Juan, H.-Y. Tung, J.-P. Wang, C.-K. Wei, Felix Wu, T.-C. Yin, T. Yu, Y. Zhuang, S.-d. Lin, H.-T. Lin, C.-J. Lin
KDD Cup 2013 Workshop, KDD 2013

Journal Paper

Effective String Processing and Matching for Author Disambiguation. [Paper]

W.-S. Chin, Y.-C. Juan, Y.-Zhuang, Felix Wu, H.-Y. Tung, T. Yu, J.-P. Wang, C.-X. Chang, C.-P. Yang, W.-C. Chang, K.-H. Huang, T.-M. Kuo, S.-W. Lin, Y.-S. Lin, Y.-\ C. Lu, Y.-C. Su, C.-K. Wei, T.- C. Yin, C.-L. Li, T.-W. Lin, C.-H. Tsai, S.-d. Lin, H.-T. Lin, C.-J. Lin
Journal of Machine Learning Research, 2014

Resume(Short version)[ Last Update: 2017/4 ]

Education


Carnegie Mellon University

2015-present

PhD Student
Machine Learning Department, School of Computer Science

Carnegie Mellon University

2013-2015

Master Student
Machine Learning Department, School of Computer Science

National Taiwan University

2009-2013

B.S. in Electrical Engineering

Work Experience


OpenAI Inc.

2018 Summer (Expected)

Research Intern

Adobe Research

2017 Summer (Expected)

Research Intern with Ersin Yumer

Google Brain, Google Inc.

2016 Summer

Software Enginnering Intern with Andrew Dai

Intel Parallel Computing Lab

2015 Summer

Research Intern with Sheng Li

MediaTek

2012 Summer

Summer Intern, Home Entertainment group

Honor and Awards


Member of Eta Kappa Nu

An academic honor society

2013 KDD Cup Award, Track1&2 Champion

The leading Data Mining competition in the world, organized by ACM.
Competition topic on Author-Paper recognition for data from Microsoft Academic Search

2 times NTU President Award

Awarded to top 5% of students in each department of National Taiwan University.
Rank 1/245 in 2012 Spring

NTU 2013 Student Outstanding Performance Scholarship

2012 Altera Innovate Asia FPGA Design Competition, Outstanding Achievement

Most prestigious FPGA design competition in Asia.
Project on FPGA-based gesture recognition 3-D control panel

2nd Place in NTU Green Grass Award (without a first prize winner)

NTU Art Festival Installation Art Contest

Projects Webpage


Adversarial Inversion: Self-supervision with Adversarial Priors

We propose adversarial inversion, a weakly supervised neural network model that combines self-supervision with adversarial constraints. Given visual input, our model first generates a set of desirable intermediate latent variables, which we call “imaginations”,e.g., 3D pose and camera viewpoint. Then a differentiable renderer projects these imaginations to reconstruct the input, and discriminator networks constrain the imaginations, using corresponding reference repositories, to reside in the right “domain” e.g., 3D human poses, camera viewpoints, 3D depth maps etc., depending on the task. Our model is trained to minimize reconstruction and adversarial losses. Adversarial inversion can be trained with or without paired supervision of standard supervised models, as it does not require paired annotations. It can instead exploit a large number of unlabelled images. We empirically show adversarial inversion outperforms previous state-of-the-art supervised models on 3D human pose estimation and 3D scene depth estimation from per-frame motion. Further, we show interesting results on biased image editing.

Contact Information

Address

GHC-8215, Gates Hillman Center,
Machine Learning Department,
Carnegie Mellon University,
5000 Forbes Ave,
Pittsburgh, PA 15213

Email

htung at cs.cmu.edu
or
sfish0101 at gmail.com

Links :