Alexander J Smola
16 papers · 2013–2023 · 1 venue · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+6 more ↓ Show less ↑
🐣 Hot Topic Early Bird 🗺️ Taxonomy Completionist (52) 🏃 Academic Marathon · Half 🌉 Interdisciplinary Bridge · Gold 🌟 Keyword Trendsetter Combo (3)
🧭
Keyword Pioneer
📈
Trend Setter
🌈
Renaissance Researcher
(6)
🔥
Unstoppable · Bronze
🗃️
Keyword Collector
(107)
💎
Century Club · Bronze
Venues
Top co-authors
Research topics
Machine Learning
(13)
Deep Learning
(10)
Optimization & Theory · Machine Learning
(10)
Optimization & Theory · Deep Learning
(7)
Mathematics & Optimization
(4)
Learning Types
(4)
Data Science & Analytics
(3)
Reinforcement Learning
(3)
Bayesian & Probabilistic
(3)
Core Methods
(3)
Methods
(3)
Optimization
(3)
Artificial Intelligence
(2)
Computer Science
(2)
Application Areas
(2)
Keywords
variance reduction
(4)
stochastic optimization
(3)
variational inference
(3)
bayesian inference
(2)
tensor decomposition
(2)
stochastic gradient
(2)
non-convex optimization
(2)
stochastic gradient descent
(2)
logistic regression
(2)
offline reinforcement learning
(1)
ensemble learning
(1)
transfer learning
(1)
bayesian nonparametrics
(1)
topic modeling
(1)
probabilistic modeling
(1)
data augmentation
(1)
model distillation
(1)
knowledge distillation
(1)
latent dirichlet allocation
(1)
finite-sum optimization
(1)
Papers
Prompt Pre-Training with Twenty-Thousand Classes for Open-Vocabulary Visual Recognition
NeurIPS 2023
Adaptive Interest for Emphatic Reinforcement Learning
NeurIPS 2022
Faster Deep Reinforcement Learning with Slower Online Network
NeurIPS 2022
Graph Reordering for Cache-Efficient Near Neighbor Search
NeurIPS 2022
Continuous Doubly Constrained Batch Reinforcement Learning
NeurIPS 2021
Deep Explicit Duration Switching Models for Time Series
NeurIPS 2021
Mixture Proportion Estimation and PU Learning:A Modern Approach
NeurIPS 2021
Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation
NeurIPS 2020
Deep Sets
NeurIPS 2017
Proximal Stochastic Methods for Nonsmooth Nonconvex Finite-Sum Optimization
NeurIPS 2016
Variance Reduction in Stochastic Gradient Langevin Dynamics
NeurIPS 2016
Fast and Guaranteed Tensor Decomposition via Sketching
NeurIPS 2015
On Variance Reduction in Stochastic Gradient Descent and its Asynchronous Variants
NeurIPS 2015
Communication Efficient Distributed Machine Learning with the Parameter Server
NeurIPS 2014
Spectral Methods for Indian Buffet Process Inference
NeurIPS 2014
Variance Reduction for Stochastic Gradient Optimization
NeurIPS 2013