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ICML 2016 & Research at Google
Monday, June 20, 2016
Posted by Afshin Rostamizadeh, Research Scientist
This week, New York hosts the
2016 International Conference on Machine Learning
(ICML 2016), a premier annual Machine Learning event supported by the
International Machine Learning Society
(IMLS). Machine Learning is a key focus area at Google, with highly active research groups exploring virtually all aspects of the field, including deep learning and more classical algorithms.
We work on an extremely wide variety of machine learning problems that arise from a broad range of applications at Google. One particularly important setting is that of large-scale learning, where we utilize scalable tools and architectures to build machine learning systems that work with large volumes of data that often preclude the use of standard single-machine training algorithms. In doing so, we are able to solve deep scientific problems and engineering challenges, exploring theory as well as application, in areas of language, speech, translation, music, visual processing and more.
As Gold Sponsor, Google has a strong presence at ICML 2016 with many Googlers publishing their research and hosting workshops. If you’re attending, we hope you’ll visit the Google booth and talk with our researchers to learn more about the exciting work, creativity and fun that goes into solving interesting ML problems that impact millions of people. You can also learn more about our research being presented at ICML 2016 in the list below (Googlers highlighted in
blue
).
ICML 2016 Organizing Committee
Area Chairs include:
Corinna Cortes
,
John Blitzer
,
Maya Gupta
,
Moritz Hardt
,
Samy Bengio
IMLS
Board Members include:
Corinna Cortes
Accepted Papers
ADIOS: Architectures Deep In Output Space
Moustapha Cisse, Maruan Al-Shedivat,
Samy Bengio
Associative Long Short-Term Memory
Ivo Danihelka (Google DeepMind)
,
Greg Wayne
(Google DeepMind)
,
Benigno Uria
(Google DeepMind)
,
Nal Kalchbrenner
(Google DeepMind)
,
Alex Graves
(Google DeepMind)
Asynchronous Methods for Deep Reinforcement Learning
Volodymyr Mnih
(Google DeepMind)
,
Adria Puigdomenech Badia
(Google DeepMind)
, Mehdi Mirza,
Alex Graves
(Google DeepMind)
,
Timothy Lillicrap
(Google DeepMind)
,
Tim Harley
(Google DeepMind)
,
David Silver
(Google DeepMind)
,
Koray Kavukcuoglu
(Google DeepMind)
Binary embeddings with structured hashed projections
Anna Choromanska,
Krzysztof Choromanski
, Mariusz Bojarski, Tony Jebara,
Sanjiv Kumar
, Yann LeCun
Discrete Distribution Estimation Under Local Privacy
Peter Kairouz,
Keith Bonawitz
,
Daniel Ramage
Dueling Network Architectures for Deep Reinforcement Learning
(Best Paper Award recipient)
Ziyu Wang
(Google DeepMind)
,
Nando de Freitas
(Google DeepMind)
,
Tom Schaul
(Google DeepMind)
,
Matteo Hessel
(Google DeepMind)
,
Hado van Hasselt
(Google DeepMind)
,
Marc Lanctot
(Google DeepMind)
Exploiting Cyclic Symmetry in Convolutional Neural Networks
Sander Dieleman
(Google DeepMind)
,
Jeffrey De Fauw
(Google DeepMind)
,
Koray Kavukcuoglu
(Google DeepMind)
Fast Constrained Submodular Maximization: Personalized Data Summarization
Baharan Mirzasoleiman,
Ashwinkumar Badanidiyuru
, Amin Karbasi
Greedy Column Subset Selection: New Bounds and Distributed Algorithms
Jason Altschuler, Aditya Bhaskara,
Gang Fu
,
Vahab Mirrokni
,
Afshin Rostamizadeh
,
Morteza Zadimoghaddam
Horizontally Scalable Submodular Maximization
Mario Lucic, Olivier Bachem,
Morteza Zadimoghaddam
, Andreas Krause
Continuous Deep Q-Learning with Model-based Acceleration
Shixiang Gu,
Timothy Lillicrap
(Google DeepMind)
,
Ilya Sutskever
,
Sergey Levine
Meta-Learning with Memory-Augmented Neural Networks
Adam Santoro
(Google DeepMind)
, Sergey Bartunov,
Matthew Botvinick
(Google DeepMind)
,
Daan Wierstra
(Google DeepMind)
,
Timothy Lillicrap
(Google DeepMind)
One-Shot Generalization in Deep Generative Models
Danilo Rezende
(Google DeepMind)
,
Shakir Mohamed
(Google DeepMind)
,
Daan Wierstra
(Google DeepMind)
Pixel Recurrent Neural Networks
(Best Paper Award recipient)
Aaron Van den Oord
(Google DeepMind)
,
Nal Kalchbrenner
(Google DeepMind)
,
Koray Kavukcuoglu
(Google DeepMind)
Pricing a low-regret seller
Hoda Heidari,
Mohammad Mahdian
,
Umar Syed
,
Sergei Vassilvitskii
, Sadra Yazdanbod
Primal-Dual Rates and Certificates
Celestine Dünner,
Simone Forte
, Martin Takac, Martin Jaggi
Recommendations as Treatments: Debiasing Learning and Evaluation
Tobias Schnabel, Thorsten Joachims, Adith Swaminathan, Ashudeep Singh,
Navin Chandak
Recycling Randomness with Structure for Sublinear Time Kernel Expansions
Krzysztof Choromanski
,
Vikas Sindhwani
Train faster, generalize better: Stability of stochastic gradient descent
Moritz Hardt
, Ben Recht,
Yoram Singer
Variational Inference for Monte Carlo Objectives
Andriy Mnih
(Google DeepMind)
,
Danilo Rezende
(Google DeepMind)
Workshops
Abstraction in Reinforcement Learning
Organizing Committee:
Daniel Mankowitz,
Timothy Mann
(Google DeepMind)
, Shie Mannor
Invited Speaker:
David Silver
(Google DeepMind)
Deep Learning Workshop
Organizers:
Antoine Bordes, Kyunghyun Cho, Emily Denton,
Nando de Freitas
(Google DeepMind)
, Rob Fergus
Invited Speaker:
Raia Hadsell
(Google DeepMind)
Neural Networks Back To The Future
Organizers:
Léon Bottou, David Grangier, Tomas Mikolov,
John Platt
Data-Efficient Machine Learning
Organizers:
Marc Deisenroth,
Shakir Mohamed
(Google DeepMind)
, Finale Doshi-Velez, Andreas Krause, Max Welling
On-Device Intelligence
Organizers:
Vikas Sindhwani
,
Daniel Ramage
,
Keith Bonawitz
, Suyog Gupta, Sachin Talathi
Invited Speakers:
Hartwig Adam
,
H. Brendan McMahan
Online Advertising Systems
Organizing Committee:
Sharat Chikkerur,
Hossein Azari
, Edoardo Airoldi
Opening Remarks:
Hossein Azari
Invited Speakers:
Martin Pál
,
Todd Phillips
Anomaly Detection 2016
Organizing Committee:
Nico Goernitz, Marius Kloft,
Vitaly Kuznetsov
Tutorials
Deep Reinforcement Learning
David Silver
(Google DeepMind)
Rigorous Data Dredging: Theory and Tools for Adaptive Data Analysis
Moritz Hardt
, Aaron Roth
ICML 2015 and Machine Learning Research at Google
Sunday, July 05, 2015
Posted by Corinna Cortes, Head, Google Research NY
This week, Lille, France hosts the
2015 International Conference on Machine Learning
(ICML 2015), a premier annual Machine Learning event supported by the
International Machine Learning Society
(IMLS). As a leader in Machine Learning research, Google will have a strong presence at ICML 2015, with many Googlers publishing work and hosting workshops. If you’re attending, we hope you’ll visit the Google booth and talk with the Googlers to learn more about the hard work, creativity and fun that goes into solving interesting ML problems that impacts millions of people. You can also learn more about our research being presented at ICML 2015 in the list below (Googlers highlighted in
blue
).
Google is a Platinum Sponsor of ICML 2015.
ICML Program Committee
Area Chair -
Corinna Cortes
&
Samy Bengio
IMLS Board Member -
Corinna Cortes
Papers:
Learning Program Embeddings to Propagate Feedback on Student Code
Chris Piech,
Jonathan Huang
, Andy Nguyen, Mike Phulsuksombati, Mehran Sahami, Leonidas Guibas
BilBOWA: Fast Bilingual Distributed Representations without Word Alignments
Stephan Gouws
, Yoshua Bengio,
Greg Corrado
An Empirical Exploration of Recurrent Network Architectures
Rafal Jozefowicz
, Wojciech Zaremba,
Ilya Sutskever
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe
,
Christian Szegedy
DRAW: A Recurrent Neural Network For Image Generation
Karol Gregor
,
Ivo Danihelka
,
Alex Graves
,
Danilo Rezende
,
Daan Wierstra
Variational Inference with Normalizing Flows
Danilo Rezende
,
Shakir Mohamed
Structural Maxent Models
Corinna Cortes
, Vitaly Kuznetsov,
Mehryar Mohri
,
Umar Syed
Weight Uncertainty in Neural Network
Charles Blundell
,
Julien Cornebise
,
Koray Kavukcuoglu
,
Daan Wierstra
MADE: Masked Autoencoder for Distribution Estimation
Mathieu Germain,
Karol Gregor
, Iain Murray, Hugo Larochelle
Fictitious Self-Play in Extensive-Form Games
Johannes Heinrich,
Marc Lanctot
,
David Silver
Universal Value Function Approximators
Tom Schaul
,
Daniel Horgan
,
Karol Gregor
,
David Silver
Workshops:
Extreme Classification: Learning with a Very Large Number of Labels
Samy Bengio
- Organizing Committee
Machine Learning for Education
Jonathan Huang
- Organizing Committee
Workshop on Machine Learning Open Source Software 2015: Open Ecosystems
Ian Goodfellow
- Program Committee
Machine Learning for Music Recommendation
Philippe Hamel
- Invited Speaker
Large-Scale Kernel Learning: Challenges and New Opportunities
Poster -
Just-In-Time Kernel Regression for Expectation Propagation
Wittawat Jitkrittum, Arthur Gretton,
Nicolas Heess
,
S.M. Ali Eslami
, Balaji Lakshminarayanan, Dino Sejdinovic, Zoltan Szabo
European Workshop on Reinforcement Learning (EWRL)
Rémi Munos
- Organizing Committee
David Silver
- Keynote
Workshop on Deep Learning
Geoff Hinton
- Organizer
Tara Sainath
,
Oriol Vinyals
,
Ian Goodfellow
,
Karol Gregor
- Invited Speakers
Poster -
A Neural Conversational Model
Oriol Vinyals
,
Quoc Le
Oral Presentation -
Massively Parallel Methods for Deep Reinforcement Learning
Arun Nair
,
Praveen Srinivasan
,
Sam Blackwell
,
Cagdas Alcicek
,
Rory Fearon
,
Alessandro De Maria
,
Vedavyas Panneershelvam
,
Mustafa Suleyman
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