Workshops

Topological Methods for Machine Learning
Convention Hall No.4A 

Jerry Zhu, Yuan Yao, Lek-Heng Lim, Jun Zhu

Workshop on Crowdsourcing and Human Computing
Convention Hall No.4B 

Adish Singla, Xi Chen, Gagan Goel, Nihar Shah, Dengyong Zhou

The 3rd Workshop on Issues of Sentiment Discovery and Opinion Mining (WISDOM)
Convention Hall No.4C 

Yunqing Xia, Erik Cambria, Yongzheng Zhang, Newton Howard

Learning, Security & Privacy
Convention Hall No.4D 

Daniel Lowd, Pavel Laskov, Christos Dimitrakakis, Benjamin Rubinstein, Elaine Shi

Designing Machine Learning Platforms for Big Data
Room 201A 

Xiangxiang Meng, Wayne Thompson, Xiaodong Lin

New Learning Frameworks and Models for Big Data
Room 201B 

Massih-Reza Amini, Eric Gaussier, James Kwok, Yiming Yang

Deep Learning Models for Emerging Big Data Applications
Room 201C

Shan Suthaharan, Jinzhu Jia

Workshop on the Method of Moments and Spectral Learning
Convention Hall No.4E 

Daniel Hsu, David Sontag, Percy Liang, Borja Balle Pigem, Byron Boots, Yoni Halpern

Causal Modeling & Machine Learning
Convention Hall No.4F 

Kun Zhang, Bernhard Schölkopf, Elias Bareinboim, Jiji Zhang

^†Machine Learning in China
Room 308 

Min-Ling Zhang, Wu-Jun Li

The AutoML
Convention Hall No.4A

Frank Hutter, Rich Caruana, Remi Bardenet, Misha Bilenko, Isabelle Guyon, Balazs Kegl, Hugo Larochelle

Unsupervised Learning for Bioacoustic Big Data
Convention Hall No.4B 

Hervé Glotin, Peter Dugan, Faicel Chamroukhi, Christopher Clark, Yann LeCun

Knowledge-Powered Deep Learning for Text Mining
Convention Hall No.4C 

Bin Gao, Scott Yih, Richard Socher, Jiang Bian

Covariance Selection & Graphical Model Structure Learning
Convention Hall No.4D 

Cho-Jui Hsieh, Peder Olsen, Inderjit S. Dhillon, Pradeep Ravikumar, Jorge Nocedal

Optimizing Customer Lifetime Value in Online Marketing
Convention Hall No.4E 

Georgios Theocharous, Mohammad Ghavamzadeh, Shie Mannor

Learning Tractable Probabilistic Models
Convention Hall No.4F 

Mathias Niepert, Pedro Domingos, Daniel Lowd

Divergence Methods for Probabilistic Inference
Room 308 

Oluwasanmi Koyejo, Jun Zhu, Mark Reid, Eric Xing

^‡(Joint with APSYS) ML Meets Systems
Room 307 

Lorenzo Alvisi, Haibo Chen

^†To take full advantage of the opportunity that ICML comes to Asia for the first time, particularly to China, a dedicated half-day workshop "Machine Learning in China" for machine learning researchers and practitioners in China is organized. This workshop would be a great chance for sharing ideas and expertise among interested participants, encouraging students and junior researchers to get suggestions and advices from senior experts, and also fostering connections and possible collaborations between Chinese and International machine learning communities. The half-day workshop will consist of 3-4 invited talks by established researchers as well as a poster session. For the convenience of communication and discussion, the working language of this workshop is Chinese although some invited talks might be given in English.

^‡To leverage the coresidence with ICML'2014, APSys 2014 will feature a special track to explore synergies between the systems and machine learning communities. This track aims to accommodate timely research in building systems for machine learning and in using machine learning methodologies to solve systems problems. Authors may mark the "ML for Systems & Systems for ML track" option during submission. Submissions in this track will be reviewed by PC experts in related areas and their acceptance will be decided separately, applying the same standards of quality and scholarship used for papers submitted to the main track.