← Authors

Jeff Schneider

54 papers · 2010–2025 · 11 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (8) 🐝 Cross-Pollinator (15) πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (15) 🌍 Conference Polyglot (11) πŸ—ΊοΈ Taxonomy Completionist (18) 🧭 Keyword Pioneer 🌟 Keyword Trendsetter Combo (4) 🧬 Topic Evolution πŸ”¬ Deep Specialist (15) 🀝 Dynamic Duo (24) πŸ—ƒοΈ Keyword Collector (61) πŸš€ Conference Pioneer ⚑ Prolific Year (5) πŸ”₯ Unstoppable (16) πŸ’Ž Century Club (54) πŸ“ˆ Trend Setter

Conferences

ICML (18) AISTATS (16) NIPS (7) ICLR (3) CORL (2) IJCAI (2) WACV (2) CVPR (1) JMLR (1) L4DC (1) UAI (1)

Top co-authors

BarnabΓ‘s PΓ³czos (24) Kirthevasan Kandasamy (11) Willie Neiswanger (8) Junier Oliva (6) Eric Xing (4) Ian Char (4) Roman Garnett (4) Tzu-kuo Huang (3) Siamak Ravanbakhsh (3) Shirley Ho (3)

Research topics

Probability (1)

Keywords

bayesian optimization (8) gaussian process (8) regret bound (5) active learning (5) hyperparameter tuning (4) offline reinforcement learning (3) multi-armed bandit (3) multi-fidelity optimization (3) distribution regression (3) black-box optimization (3) kernel methods (3) autonomous driving (3) divergence estimation (2) thompson sampling (2) reward function (2) spectral learning (2) convex optimization (2) nonparametric estimation (2) multi-label classification (2) domain adaptation (2)

Papers

Multi-Timescale Dynamics Model Bayesian Optimization for Plasma Stabilization in Tokamaks ICML 2025
Training a Generally Curious Agent ICML 2025
Diffusion-ES: Gradient-free Planning with Diffusion for Autonomous and Instruction-guided Driving CVPR 2024
Reasoning with Latent Diffusion in Offline Reinforcement Learning ICLR 2024
Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data ICML 2024
Sampling-based Multi-dimensional Recalibration ICML 2024
Genetic Algorithm for Curriculum Design in Multi-Agent Reinforcement Learning CORL 2024
Near-optimal Policy Identification in Active Reinforcement Learning ICLR 2023
Stealthy Terrain-Aware Multi-Agent Active Search CORL 2023
Offline Model-Based Reinforcement Learning for Tokamak Control L4DC 2023
Learning Temporally AbstractWorld Models without Online Experimentation ICML 2023
SBEVNet: End-to-End Deep Stereo Layout Estimation WACV 2022
An Experimental Design Perspective on Model-Based Reinforcement Learning ICLR 2022
Addressing Optimism Bias in Sequence Modeling for Reinforcement Learning ICML 2022
Decentralized multi-agent active search for sparse signals UAI 2021
ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations AISTATS 2020
Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly JMLR 2020
Uncertainty-aware Short-term Motion Prediction of Traffic Actors for Autonomous Driving WACV 2020
Myopic Posterior Sampling for Adaptive Goal Oriented Design of Experiments ICML 2019
Offline Contextual Bayesian Optimization NIPS 2019
Parallelised Bayesian Optimisation via Thompson Sampling AISTATS 2018
Transformation Autoregressive Networks ICML 2018
Neural Architecture Search with Bayesian Optimisation and Optimal Transport NIPS 2018
The Statistical Recurrent Unit ICML 2017
Equivariance Through Parameter-Sharing ICML 2017
Scaling Active Search using Linear Similarity Functions IJCAI 2017
Multi-fidelity Bayesian Optimisation with Continuous Approximations ICML 2017
High Dimensional Bayesian Optimization via Restricted Projection Pursuit Models AISTATS 2016
The Multi-fidelity Multi-armed Bandit NIPS 2016
Gaussian Process Bandit Optimisation with Multi-fidelity Evaluations NIPS 2016
Stochastic Neural Networks with Monotonic Activation Functions AISTATS 2016
Bayesian Nonparametric Kernel-Learning AISTATS 2016
Estimating Cosmological Parameters from the Dark Matter Distribution ICML 2016
Nonparametric Risk and Stability Analysis for Multi-Task Learning Problems IJCAI 2016
Finding Galaxies in the Shadows of Quasars with Gaussian Processes ICML 2015
Fast Function to Function Regression AISTATS 2015
Active Pointillistic Pattern Search AISTATS 2015
High Dimensional Bayesian Optimisation and Bandits via Additive Models ICML 2015
Fast Distribution To Real Regression AISTATS 2014
Active Area Search via Bayesian Quadrature AISTATS 2014
Flexible Transfer Learning under Support and Model Shift NIPS 2014
Active Transfer Learning under Model Shift ICML 2014
FuSSO: Functional Shrinkage and Selection Operator AISTATS 2014
Spectral Learning of Hidden Markov Models from Dynamic and Static Data ICML 2013
Ξ£-Optimality for Active Learning on Gaussian Random Fields NIPS 2013
Learning Hidden Markov Models from Non-sequence Data via Tensor Decomposition NIPS 2013
Expensive Function Optimization with Stochastic Binary Outcomes ICML 2013
Distribution to Distribution Regression ICML 2013
A Composite Likelihood View for Multi-Label Classification AISTATS 2012
Nonparametric Estimation of Conditional Information and Divergences AISTATS 2012
Multi-Label Output Codes using Canonical Correlation Analysis AISTATS 2011
Hierarchical Probabilistic Models for Group Anomaly Detection AISTATS 2011
On the Estimation of $\alpha$-Divergences AISTATS 2011
Learning Nonlinear Dynamic Models from Non-sequenced Data AISTATS 2010