Alexander J. Smola

ORCID

Publication Activity (10 Years)

Years Active: 1996-2023
Publications (10 Years): 122

Top Venues

Technical University of Berlin, Germany (PHD)

Education History

Technical University of Berlin, Germany

PHD

Publications

Shuhuai Ren, Aston Zhang, Yi Zhu, Shuai Zhang, Shuai Zheng, Mu Li, Alexander J. Smola, Xu Sun
Prompt Pre-Training with Twenty-Thousand Classes for Open-Vocabulary Visual Recognition. NeurIPS (2023)
Rasool Fakoor, Taesup Kim, Jonas Mueller, Alexander J. Smola, Ryan J. Tibshirani
Flexible Model Aggregation for Quantile Regression. J. Mach. Learn. Res. 24 (2023)
Hang Zhang, Chongruo Wu, Zhongyue Zhang, Yi Zhu, Haibin Lin, Zhi Zhang, Yue Sun, Tong He, Jonas Mueller, R. Manmatha, Mu Li, Alexander J. Smola
ResNeSt: Split-Attention Networks. CVPR Workshops (2022)
Gaurav Gupta, Tharun Medini, Anshumali Shrivastava, Alexander J. Smola
BLISS: A Billion scale Index using Iterative Re-partitioning. KDD (2022)
Kavosh Asadi, Rasool Fakoor, Omer Gottesman, Taesup Kim, Michael L. Littman, Alexander J. Smola
Faster Deep Reinforcement Learning with Slower Online Network. NeurIPS (2022)
Jiarui Jin, Kounianhua Du, Weinan Zhang, Jiarui Qin, Yuchen Fang, Yong Yu, Zheng Zhang, Alexander J. Smola
GraphHINGE: Learning Interaction Models of Structured Neighborhood on Heterogeneous Information Network. ACM Trans. Inf. Syst. 40 (3) (2022)
Benjamin Coleman, Santiago Segarra, Alexander J. Smola, Anshumali Shrivastava
Graph Reordering for Cache-Efficient Near Neighbor Search. NeurIPS (2022)
Nick Erickson, Xingjian Shi, James Sharpnack, Alexander J. Smola
Multimodal AutoML for Image, Text and Tabular Data. KDD (2022)
Rasool Fakoor, Jonas Mueller, Zachary C. Lipton, Pratik Chaudhari, Alexander J. Smola
Data drift correction via time-varying importance weight estimator. CoRR (2022)
Martin Klissarov, Rasool Fakoor, Jonas W. Mueller, Kavosh Asadi, Taesup Kim, Alexander J. Smola
Adaptive Interest for Emphatic Reinforcement Learning. NeurIPS (2022)
Kavosh Asadi, Rasool Fakoor, Omer Gottesman, Michael L. Littman, Alexander J. Smola
Deep Q-Network with Proximal Iteration. CoRR (2021)
Rasool Fakoor, Jonas Mueller, Pratik Chaudhari, Alexander J. Smola
Continuous Doubly Constrained Batch Reinforcement Learning. CoRR (2021)
Xingjian Shi, Jonas Mueller, Nick Erickson, Mu Li, Alexander J. Smola
Benchmarking Multimodal AutoML for Tabular Data with Text Fields. CoRR (2021)
Rasool Fakoor, Jonas Mueller, Kavosh Asadi, Pratik Chaudhari, Alexander J. Smola
Continuous Doubly Constrained Batch Reinforcement Learning. NeurIPS (2021)
Saurabh Garg, Yifan Wu, Alexander J. Smola, Sivaraman Balakrishnan, Zachary C. Lipton
Mixture Proportion Estimation and PU Learning: A Modern Approach. NeurIPS (2021)
Gaurav Gupta, Tharun Medini, Anshumali Shrivastava, Alexander J. Smola
IRLI: Iterative Re-partitioning for Learning to Index. CoRR (2021)
Xingjian Shi, Jonas Mueller, Nick Erickson, Mu Li, Alexander J. Smola
Benchmarking Multimodal AutoML for Tabular Data with Text Fields. NeurIPS Datasets and Benchmarks (2021)
Abdul Fatir Ansari, Konstantinos Benidis, Richard Kurle, Ali Caner Türkmen, Harold Soh, Alexander J. Smola, Yuyang Wang, Tim Januschowski
Deep Explicit Duration Switching Models for Time Series. CoRR (2021)
Aashiq Muhamed, Liang Li, Xingjian Shi, Suri Yaddanapudi, Wayne Chi, Dylan Jackson, Rahul Suresh, Zachary C. Lipton, Alexander J. Smola
Symbolic Music Generation with Transformer-GANs. AAAI (2021)
Abdul Fatir Ansari, Konstantinos Benidis, Richard Kurle, Ali Caner Türkmen, Harold Soh, Alexander J. Smola, Bernie Wang, Tim Januschowski
Deep Explicit Duration Switching Models for Time Series. NeurIPS (2021)
Aston Zhang, Zachary C. Lipton, Mu Li, Alexander J. Smola
Dive into Deep Learning. CoRR (2021)
Taesup Kim, Rasool Fakoor, Jonas Mueller, Alexander J. Smola, Ryan J. Tibshirani
Deep Quantile Aggregation. CoRR (2021)
Rasool Fakoor, Jonas Mueller, Nick Erickson, Pratik Chaudhari, Alexander J. Smola
Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation. NeurIPS (2020)
Rasool Fakoor, Pratik Chaudhari, Jonas Mueller, Alexander J. Smola
TraDE: Transformers for Density Estimation. CoRR (2020)
Jonas Mueller, Xingjian Shi, Alexander J. Smola
Faster, Simpler, More Accurate: Practical Automated Machine Learning with Tabular, Text, and Image Data. KDD (2020)
Rasool Fakoor, Pratik Chaudhari, Stefano Soatto, Alexander J. Smola
Meta-Q-Learning. ICLR (2020)
Jiarui Jin, Jiarui Qin, Yuchen Fang, Kounianhua Du, Weinan Zhang, Yong Yu, Zheng Zhang, Alexander J. Smola
An Efficient Neighborhood-based Interaction Model for Recommendation on Heterogeneous Graph. KDD (2020)
Nick Erickson, Jonas Mueller, Alexander Shirkov, Hang Zhang, Pedro Larroy, Mu Li, Alexander J. Smola
AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data. CoRR (2020)
Yi Zhu, Zhongyue Zhang, Chongruo Wu, Zhi Zhang, Tong He, Hang Zhang, R. Manmatha, Mu Li, Alexander J. Smola
Improving Semantic Segmentation via Self-Training. CoRR (2020)
Hang Zhang, Chongruo Wu, Zhongyue Zhang, Yi Zhu, Zhi Zhang, Haibin Lin, Yue Sun, Tong He, Jonas Mueller, R. Manmatha, Mu Li, Alexander J. Smola
ResNeSt: Split-Attention Networks. CoRR (2020)
Jiarui Jin, Jiarui Qin, Yuchen Fang, Kounianhua Du, Weinan Zhang, Yong Yu, Zheng Zhang, Alexander J. Smola
An Efficient Neighborhood-based Interaction Model for Recommendation on Heterogeneous Graph. CoRR (2020)
Rasool Fakoor, Pratik Chaudhari, Alexander J. Smola
DDPG++: Striving for Simplicity in Continuous-control Off-Policy Reinforcement Learning. CoRR (2020)
Louis Abraham, Gary Bécigneul, Benjamin Coleman, Bernhard Schölkopf, Anshumali Shrivastava, Alexander J. Smola
Bloom Origami Assays: Practical Group Testing. CoRR (2020)
Jiarui Jin, Kounianhua Du, Weinan Zhang, Jiarui Qin, Yuchen Fang, Yong Yu, Zheng Zhang, Alexander J. Smola
Learning Interaction Models of Structured Neighborhood on Heterogeneous Information Network. CoRR (2020)
Rasool Fakoor, Jonas Mueller, Nick Erickson, Pratik Chaudhari, Alexander J. Smola
Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation. CoRR (2020)
Chenguang Wang, Zihao Ye, Aston Zhang, Zheng Zhang, Alexander J. Smola
Transformer on a Diet. CoRR (2020)
Han Zhao, Otilia Stretcu, Alexander J. Smola, Geoffrey J. Gordon
Efficient Multitask Feature and Relationship Learning. UAI (2019)
Chenguang Wang, Mu Li, Alexander J. Smola
Language Models with Transformers. CoRR (2019)
Minjie Wang, Lingfan Yu, Da Zheng, Quan Gan, Yu Gai, Zihao Ye, Mufei Li, Jinjing Zhou, Qi Huang, Chao Ma, Ziyue Huang, Qipeng Guo, Hao Zhang, Haibin Lin, Junbo Zhao, Jinyang Li, Alexander J. Smola, Zheng Zhang
Deep Graph Library: Towards Efficient and Scalable Deep Learning on Graphs. CoRR (2019)
Ali Caner Türkmen, Yuyang Wang, Alexander J. Smola
FastPoint: Scalable Deep Point Processes. ECML/PKDD (2) (2019)
Rasool Fakoor, Pratik Chaudhari, Alexander J. Smola
P3O: Policy-on Policy-off Policy Optimization. UAI (2019)
Rasool Fakoor, Pratik Chaudhari, Alexander J. Smola
P3O: Policy-on Policy-off Policy Optimization. CoRR (2019)
Haibin Lin, Xingjian Shi, Leonard Lausen, Aston Zhang, He He, Sheng Zha, Alexander J. Smola
Dive into Deep Learning for Natural Language Processing. EMNLP/IJCNLP (2) (2019)
Rasool Fakoor, Pratik Chaudhari, Stefano Soatto, Alexander J. Smola
Meta-Q-Learning. CoRR (2019)
Sashank J. Reddi, Manzil Zaheer, Suvrit Sra, Barnabás Póczos, Francis R. Bach, Ruslan Salakhutdinov, Alexander J. Smola
A Generic Approach for Escaping Saddle points. AISTATS (2018)
Zachary C. Lipton, Yu-Xiang Wang, Alexander J. Smola
Detecting and Correcting for Label Shift with Black Box Predictors. CoRR (2018)
Hanjun Dai, Zornitsa Kozareva, Bo Dai, Alexander J. Smola, Le Song
Learning Steady-States of Iterative Algorithms over Graphs. ICML (2018)
Zachary C. Lipton, Yu-Xiang Wang, Alexander J. Smola
Detecting and Correcting for Label Shift with Black Box Predictors. ICML (2018)
Yuyu Zhang, Hanjun Dai, Zornitsa Kozareva, Alexander J. Smola, Le Song
Variational Reasoning for Question Answering With Knowledge Graph. AAAI (2018)
Chao-Yuan Wu, Manzil Zaheer, Hexiang Hu, R. Manmatha, Alexander J. Smola, Philipp Krähenbühl
Compressed Video Action Recognition. CVPR (2018)
Chao-Yuan Wu, Manzil Zaheer, Hexiang Hu, R. Manmatha, Alexander J. Smola, Philipp Krähenbühl
Compressed Video Action Recognition. CoRR (2017)
Joachim Curto, Irene Zarza, Alexander J. Smola, Luc Van Gool
HashBox: Hash Hierarchical Segmentation exploiting Bounding Box Object Detection. CoRR (2017)
Xun Zheng, Manzil Zaheer, Amr Ahmed, Yuan Wang, Eric P. Xing, Alexander J. Smola
State Space LSTM Models with Particle MCMC Inference. CoRR (2017)
Sashank J. Reddi, Manzil Zaheer, Suvrit Sra, Barnabás Póczos, Francis R. Bach, Ruslan Salakhutdinov, Alexander J. Smola
A Generic Approach for Escaping Saddle points. CoRR (2017)
Hsiao-Yu Fish Tung, Chao-Yuan Wu, Manzil Zaheer, Alexander J. Smola
Spectral Methods for Nonparametric Models. CoRR (2017)
Chao-Yuan Wu, R. Manmatha, Alexander J. Smola, Philipp Krähenbühl
Sampling Matters in Deep Embedding Learning. CoRR (2017)
Travis Dick, Mu Li, Venkata Krishna Pillutla, Colin White, Maria-Florina Balcan, Alexander J. Smola
Data Driven Resource Allocation for Distributed Learning. AAAI Workshops (2017)
Travis Dick, Mu Li, Venkata Krishna Pillutla, Colin White, Nina Balcan, Alexander J. Smola
Data Driven Resource Allocation for Distributed Learning. AISTATS (2017)
Manzil Zaheer, Satwik Kottur, Siamak Ravanbakhsh, Barnabás Póczos, Ruslan Salakhutdinov, Alexander J. Smola
Deep Sets. NIPS (2017)
Manzil Zaheer, Satwik Kottur, Amr Ahmed, José M. F. Moura, Alexander J. Smola
Canopy Fast Sampling with Cover Trees. ICML (2017)
R. Manmatha, Chao-Yuan Wu, Alexander J. Smola, Philipp Krähenbühl
Sampling Matters in Deep Embedding Learning. ICCV (2017)
Han Zhao, Otilia Stretcu, Renato Negrinho, Alexander J. Smola, Geoffrey J. Gordon
Efficient Multi-task Feature and Relationship Learning. CoRR (2017)
Chao-Yuan Wu, Amr Ahmed, Alex Beutel, Alexander J. Smola
Joint Training of Ratings and Reviews with Recurrent Recommender Networks. ICLR (Workshop) (2017)
How Jing, Alexander J. Smola
Neural Survival Recommender. WSDM (2017)
Yuyu Zhang, Hanjun Dai, Zornitsa Kozareva, Alexander J. Smola, Le Song
Variational Reasoning for Question Answering with Knowledge Graph. CoRR (2017)
Danica J. Sutherland, Hsiao-Yu Tung, Heiko Strathmann, Soumyajit De, Aaditya Ramdas, Alexander J. Smola, Arthur Gretton
Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy. ICLR (Poster) (2017)
Manzil Zaheer, Amr Ahmed, Alexander J. Smola
Latent LSTM Allocation: Joint Clustering and Non-Linear Dynamic Modeling of Sequence Data. ICML (2017)
Zichao Yang, Zhiting Hu, Yuntian Deng, Chris Dyer, Alexander J. Smola
Neural Machine Translation with Recurrent Attention Modeling. EACL (2) (2017)
Chao-Yuan Wu, Amr Ahmed, Alex Beutel, Alexander J. Smola, How Jing
Recurrent Recommender Networks. WSDM (2017)
Manzil Zaheer, Satwik Kottur, Siamak Ravanbakhsh, Barnabás Póczos, Ruslan Salakhutdinov, Alexander J. Smola
Deep Sets. CoRR (2017)
Ziqi Liu, Alexander J. Smola, Kyle Soska, Yu-Xiang Wang, Qinghua Zheng
Attributing Hacks. AISTATS (2017)
Joachim Curto, Irene Zarza, Feng Yang, Alexander J. Smola, Luc Van Gool
F2F: A Library For Fast Kernel Expansions. CoRR (2017)
Rajarshi Das, Shehzaad Dhuliawala, Manzil Zaheer, Luke Vilnis, Ishan Durugkar, Akshay Krishnamurthy, Alexander J. Smola, Andrew McCallum
Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning. CoRR (2017)
Ziqi Liu, Alexander J. Smola, Kyle Soska, Yu-Xiang Wang, Qinghua Zheng
Attributing Hacks. CoRR (2016)
Seth R. Flaxman, Daniel B. Neill, Alexander J. Smola
Gaussian Processes for Independence Tests with Non-iid Data in Causal Inference. ACM Trans. Intell. Syst. Technol. 7 (2) (2016)
Chao-Yuan Wu, Christopher V. Alvino, Alexander J. Smola, Justin Basilico
Using Navigation to Improve Recommendations in Real-Time. RecSys (2016)
Sashank J. Reddi, Ahmed Hefny, Suvrit Sra, Barnabás Póczos, Alexander J. Smola
Stochastic Variance Reduction for Nonconvex Optimization. CoRR (2016)
Chao-Yuan Wu, Alex Beutel, Amr Ahmed, Alexander J. Smola
Explaining Reviews and Ratings with PACO: Poisson Additive Co-Clustering. WWW (Companion Volume) (2016)
Mu Li, Ziqi Liu, Alexander J. Smola, Yu-Xiang Wang
DiFacto: Distributed Factorization Machines. WSDM (2016)
Manzil Zaheer, Michael L. Wick, Jean-Baptiste Tristan, Alexander J. Smola, Guy L. Steele Jr.
Exponential Stochastic Cellular Automata for Massively Parallel Inference. AISTATS (2016)
Zichao Yang, Zhiting Hu, Yuntian Deng, Chris Dyer, Alexander J. Smola
Neural Machine Translation with Recurrent Attention Modeling. CoRR (2016)
Sashank J. Reddi, Suvrit Sra, Barnabás Póczos, Alexander J. Smola
Stochastic Frank-Wolfe Methods for Nonconvex Optimization. CoRR (2016)
Sashank J. Reddi, Suvrit Sra, Barnabás Póczos, Alexander J. Smola
Proximal Stochastic Methods for Nonsmooth Nonconvex Finite-Sum Optimization. NIPS (2016)
Sashank J. Reddi, Suvrit Sra, Barnabás Póczos, Alexander J. Smola
Stochastic Frank-Wolfe methods for nonconvex optimization. Allerton (2016)
Kumar Avinava Dubey, Sashank J. Reddi, Sinead A. Williamson, Barnabás Póczos, Alexander J. Smola, Eric P. Xing
Variance Reduction in Stochastic Gradient Langevin Dynamics. NIPS (2016)
Danica J. Sutherland, Hsiao-Yu Fish Tung, Heiko Strathmann, Soumyajit De, Aaditya Ramdas, Alexander J. Smola, Arthur Gretton
Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy. CoRR (2016)
Sashank J. Reddi, Suvrit Sra, Barnabás Póczos, Alexander J. Smola
Fast incremental method for smooth nonconvex optimization. CDC (2016)
Sashank J. Reddi, Ahmed Hefny, Suvrit Sra, Barnabás Póczos, Alexander J. Smola
Stochastic Variance Reduction for Nonconvex Optimization. ICML (2016)
Sashank J. Reddi, Suvrit Sra, Barnabás Póczos, Alexander J. Smola
Fast Incremental Method for Nonconvex Optimization. CoRR (2016)
Suvrit Sra, Adams Wei Yu, Mu Li, Alexander J. Smola
AdaDelay: Delay Adaptive Distributed Stochastic Optimization. AISTATS (2016)
Yu-Xiang Wang, James Sharpnack, Alexander J. Smola, Ryan J. Tibshirani
Trend Filtering on Graphs. J. Mach. Learn. Res. 17 (2016)
Zichao Yang, Diyi Yang, Chris Dyer, Xiaodong He, Alexander J. Smola, Eduard H. Hovy
Hierarchical Attention Networks for Document Classification. HLT-NAACL (2016)
Sashank J. Reddi, Jakub Konecný, Peter Richtárik, Barnabás Póczos, Alexander J. Smola
AIDE: Fast and Communication Efficient Distributed Optimization. CoRR (2016)
Sashank J. Reddi, Suvrit Sra, Barnabás Póczos, Alexander J. Smola
Fast Stochastic Methods for Nonsmooth Nonconvex Optimization. CoRR (2016)
Zichao Yang, Xiaodong He, Jianfeng Gao, Li Deng, Alexander J. Smola
Stacked Attention Networks for Image Question Answering. CVPR (2016)
Li Zhou, David G. Andersen, Mu Li, Alexander J. Smola
Cuckoo Linear Algebra. KDD (2015)
Alex Beutel, Amr Ahmed, Alexander J. Smola
ACCAMS: Additive Co-Clustering to Approximate Matrices Succinctly. WWW (2015)
Yining Wang, Hsiao-Yu Fish Tung, Alexander J. Smola, Animashree Anandkumar
Fast and Guaranteed Tensor Decomposition via Sketching. CoRR (2015)
Yu-Xiang Wang, Stephen E. Fienberg, Alexander J. Smola
Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo. ICML (2015)
Nan Du, Mehrdad Farajtabar, Amr Ahmed, Alexander J. Smola, Le Song
Dirichlet-Hawkes Processes with Applications to Clustering Continuous-Time Document Streams. KDD (2015)

Alexander J. Smola.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Alexander J. Smola