NewEvery arXiv paper, its researchers & institutions — mapped.
papers

Publications (28)

math.OC2016

Stochastic Variance Reduction for Nonconvex Optimization

Sashank J. Reddi, Ahmed Hefny, Suvrit Sra +2

cs.LG2019

Efficient Multitask Feature and Relationship Learning

Han Zhao, Otilia Stretcu, Alex Smola +1

math.OC2016

Stochastic Frank-Wolfe Methods for Nonconvex Optimization

Sashank J. Reddi, Suvrit Sra, Barnabas Poczos +1

cs.NE2016

Neural Machine Translation with Recurrent Attention Modeling

Zichao Yang, Zhiting Hu, Yuntian Deng +2

cs.LG2016

On Variance Reduction in Stochastic Gradient Descent and its Asynchronous Variants

Sashank J. Reddi, Ahmed Hefny, Suvrit Sra +2

cs.LG2016

Stacked Attention Networks for Image Question Answering

Zichao Yang, Xiaodong He, Jianfeng Gao +2

cs.LG2018

Detecting and Correcting for Label Shift with Black Box Predictors

Zachary C. Lipton, Yu-Xiang Wang, Alex Smola

stat.ML2015

Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo

Yu-Xiang Wang, Stephen E. Fienberg, Alex Smola

cs.AI2010

Feature Hashing for Large Scale Multitask Learning

Kilian Weinberger, Anirban Dasgupta, Josh Attenberg +2

cs.LG2015

Deep Fried Convnets

Zichao Yang, Marcin Moczulski, Misha Denil +4

stat.ML2019

Deep Factors for Forecasting

Yuyang Wang, Alex Smola, Danielle C. Maddix +3

cs.LG2012

Regret Bounds for Deterministic Gaussian Process Bandits

Nando de Freitas, Alex Smola, Masrour Zoghi

cs.LG2018

Deep Graphs

Emmanouil Antonios Platanios, Alex Smola

math.OC2016

Fast Stochastic Methods for Nonsmooth Nonconvex Optimization

Sashank J. Reddi, Suvrit Sra, Barnabas Poczos +1

cs.DB2012

Hokusai - Sketching Streams in Real Time

Sergiy Matusevych, Alex Smola, Amr Ahmed

cs.LG2012

Exponential Regret Bounds for Gaussian Process Bandits with Deterministic Observations

Nando de Freitas, Alex Smola, Masrour Zoghi

cs.LG2011

Parallel Online Learning

Daniel Hsu, Nikos Karampatziakis, John Langford +1

stat.ML2018

Deep Factors with Gaussian Processes for Forecasting

Danielle C. Maddix, Yuyang Wang, Alex Smola

cs.LG2012

Exponential Families for Conditional Random Fields

Yasemin Altun, Alex Smola, Thomas Hofmann

cs.CL2018

Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning

Rajarshi Das, Shehzaad Dhuliawala, Manzil Zaheer +5

math.OC2016

AIDE: Fast and Communication Efficient Distributed Optimization

Sashank J. Reddi, Jakub Konečný, Peter Richtárik +2

cs.LG2007

Supervised Feature Selection via Dependence Estimation

Le Song, Alex Smola, Arthur Gretton +2

stat.ML2014

Randomized Nonlinear Component Analysis

David Lopez-Paz, Suvrit Sra, Alex Smola +2

cs.LG2016

Data Driven Resource Allocation for Distributed Learning

Travis Dick, Mu Li, Venkata Krishna Pillutla +3

math.OC2016

Fast Incremental Method for Nonconvex Optimization

Sashank J. Reddi, Suvrit Sra, Barnabas Poczos +1

cs.LG2012

Super-Samples from Kernel Herding

Yutian Chen, Max Welling, Alex Smola

stat.ML2016

Trend Filtering on Graphs

Yu-Xiang Wang, James Sharpnack, Alex Smola +1

stat.ML2014

The Falling Factorial Basis and Its Statistical Applications

Yu-Xiang Wang, Alex Smola, Ryan J. Tibshirani