Workshop

Adaptive Experimental Design and Active Learning in the Real World

Willie Neiswanger · Mojmir Mutny · Ilija Bogunovic · Ava Amini · Zi Wang · Stefano Ermon · Andreas Krause

Project Page

Abstract

Join us for an insightful workshop on adaptive experimental design and active learning. Dive into their use in fields like computational biology, materials discovery, chip design, and more.

Video

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Schedule

Timezone: America/Los_Angeles

6:15 AM

Doors Open and Workshop/Poster Setup Setup

6:30 AM

Opening Remarks Remarks

Video

6:40 AM

High-throughput Protein Design and Evolution for Synthetic Biology - Erika DeBenedictis Invited Talk

Video

7:20 AM

From Theory to Impact: Unlocking the Power of Bayesian Optimization on Real-World Science and Engineering Systems - Joel Paulson Invited Talk

Video

8:00 AM

Coffee Break Coffee Break

8:20 AM

Adaptive Clinical Trials: Reinforcement Learning's Most Formidable Challenge - Mihaela van der Schaar Invited Talk

Video

9:00 AM

Near-Optimal Non-Parametric Sequential Tests and Confidence Sequences with Possibly Dependent Observations - Nathan Kallus Invited Talk

Video

9:40 AM

Poster Session and Lunch Poster Session

11:20 AM

Invited Talk 5: Emma Brunskill Invited Talk

Video

12:00 PM

Best Paper Candidate Spotlight Talks Spotlight Talks

Video

1:10 PM

Coffee Break Coffee Break

1:30 PM

Adaptive Experimentation without an Objective - Eytan Bakshy Invited Talk

Video

2:10 PM

RL in the Real World: From Chip Design to LLMs - Anna Goldie Invited Talk

Video

2:50 PM

Best Paper Award and Closing Remarks Remarks

Video

3:00 PM

Poster Session Poster Session

Model-Free Preference Elicitation Poster

Carlos Martin · Craig Boutilier · Ofer Meshi

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Active Learning for Iterative Offline Reinforcement Learning Poster

Lan Zhang · Luigi Franco Tedesco · Pankaj Rajak · Youcef Zemmouri · Hakan Brunzell

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Transferable Candidate Proposal with Bounded Uncertainty Poster

Kyeongryeol Go · Kye-Hyeon Kim

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Sequentially Adaptive Experimentation for Learning Optimal Options subject to Unobserved Contexts Poster

Hongju Park · Mohamad Kazem Shirani Faradonbeh

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Decentralized Multi-Agent Active Search and Tracking when Targets Outnumber Agents Poster

Arundhati Banerjee · Jeff Schneider

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Anytime-Valid Inference in Adaptive Experiments Poster

Thomas Cook · Alan Mishler · Aaditya Ramdas

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Class Balanced Dynamic Acquisition for Domain Adaptive Semantic Segmentation using Active Learning Poster

Marc Schachtsiek · Simone Rossi · Thomas Hannagan

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Pure Exploration under Mediators’ Feedback Poster

Riccardo Poiani · Alberto Maria Metelli · Marcello Restelli

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DISTRIBUTIONALLY ROBUST MODEL-BASED REINFORCEMENT LEARNING WITH LARGE STATE SPACES Poster

Shyam Sundhar Ramesh · Pier Giuseppe Sessa · Yifan Hu · Andreas Krause · Ilija Bogunovic

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Sustainable Concrete via Bayesian Optimization Poster

Sebastian Ament · Andrew Witte · Nishant Garg · Julius Kusuma

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Active Model Selection: A Variance Minimization Approach Poster

Mitsuru Matsuura · Satoshi Hara

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Preference-Guided Bayesian Optimization for Control Policy Learning: Application to Personalized Plasma Medicine Poster

Ketong Shao · Diego Romeres · Ankush Chakrabarty · Ali Mesbah

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Residual Deep Gaussian Processes on Manifolds for Geometry-aware Bayesian Optimization on Hyperspheres Poster

Kacper Wyrwal · Slava Borovitskiy

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Exploratory Training: When Annotators Learn About Data Poster

Rajesh Shrestha · Omeed Habibelahian · Arash Termehchy · Paolo Papotti

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Graph Neural Bayesian Optimization for Virtual Screening Poster

Miles Wang-Henderson · Bartu Soyuer · Parnian Kassraie · Andreas Krause · Ilija Bogunovic

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Zooming Optimistic Optimization Method to solve the Threshold Estimation Problem Poster

Julien Audiffren

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Hessian-Free Laplace in Bayesian Deep Learning Poster

James McInerney · Nathan Kallus

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On Complex Network Dynamics of an In-Vitro Neuronal System during Rest and Gameplay Poster

Moein Khajehnejad · Forough Habibollahi · Alon Loeffler · Brett J. Kagan · Adeel Razi

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Human-in-the-Loop Out-of-Distribution Detection with False Positive Rate Control Poster

Harit Vishwakarma · Heguang Lin · Ramya Korlakai Vinayak

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Cross-Entropy Estimators for Sequential Experiment Design with Reinforcement Learning Poster

Tom Blau · Iadine Chades · Amir Dezfouli · Daniel Steinberg · Edwin Bonilla

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Correlated Trajectory Uncertainty for Adaptive Sequential Decision Making Poster

Ian Char · Youngseog Chung · Rohan Shah · Willie Neiswanger · Jeff Schneider

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Efficient and scalable reinforcement learning via Hypermodel Poster

Yingru Li · Jiawei Xu · Zhi-Quan Luo

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ALAS: Active Learning for Autoconversion Rates Prediction from Satellite Data Poster

Maria Carolina Novitasari · Johannes Quaas · Miguel Rodrigues

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Near-equivalence between bounded regret and delay robustness in interactive decision making Poster

Enoch H. Kang · P. R. Kumar

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Expert-guided Bayesian Optimisation for Human-in-the-loop Experimental Design of Known Systems Poster

Tom Savage · Antonio del Rio Chanona

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Active Testing of Binary Classification Model Using Level Set Estimation Poster

Takuma Ochiai · Keiichiro Seno · Kota Matsui · Satoshi Hara

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Nonparametric Discrete Choice Experiments with Machine Learning Guided Adaptive Design Poster

Mingzhang Yin · Ruijiang Gao · Weiran Lin · Steven Shugan

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Active Learning Policies for Solving Inverse Problems Poster

Tim Bakker · Thomas Hehn · Tribhuvanesh Orekondy · Arash Behboodi · Fabio Valerio Massoli

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Physics-Enhanced Multi-fidelity Learning for Optical Surface Imprint Poster

Yongchao Chen

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Generalized Objectives in Adaptive Experimentation: The Frontier between Within- and Post-Experiment Objectives Poster

Chao Qin · Daniel Russo

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ExPT: Scaling Foundation Models for Experimental Design via Synthetic Pretraining Poster

Tung Nguyen · Sudhanshu Agrawal · Aditya Grover

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AutODEx: Automated Optimal Design of Experiments Platform with Data- and Time-Efficient Multi-Objective Optimization Poster

Yunsheng Tian · Pavle Konakovic · Beichen Li · Ane Zuniga · Michael Foshey · Timothy Erps · Wojciech Matusik · Mina Konakovic Lukovic

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Accelerated High-Entropy Alloys Discovery for Electrocatalysis via Robotic-Aided Active Learning Poster

Zhichu Ren · Zhen Zhang · Yunsheng Tian · Ju Li

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Long-run Behaviour of Multi-fidelity Bayesian Optimisation Poster

Gbetondji Dovonon · Jakob Zeitler

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Understanding Threshold-based Auto-labeling: The Good, the Bad, and the Terra Incognita Poster

Harit Vishwakarma · Heguang Lin · Frederic Sala · Ramya Korlakai Vinayak

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Probabilistic Generative Modeling for Procedural Roundabout Generation for Developing Countries Poster

Zarif Ikram · Ling Pan · Dianbo Liu

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Efficient Variational Sequential Information Control Poster

Jianwei Shen · Jason Pacheco

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Anytime Model Selection in Linear Bandits Poster

Parnian Kassraie · Nicolas Emmenegger · Andreas Krause · Aldo Pacchiano

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Multi-Fidelity Active Learning with GFlowNets Poster

Alex Hernandez-Garcia · Nikita Saxena · Moksh Jain · Chenghao Liu · Yoshua Bengio

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Learning in Clinical Trial Settings Poster

Zoe Fowler · Kiran Kokilepersaud · Mohit Prabhushankar · Ghassan AlRegib

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Preferential Heteroscedastic Bayesian Optimization with Informative Noise Priors Poster

Marshal Sinaga · Julien Martinelli · Samuel Kaski

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Optimistic Games for Combinatorial Bayesian Optimization with Applications to Protein Design Poster

Melis Ilayda Bal · Pier Giuseppe Sessa · Mojmir Mutny · Andreas Krause

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NPC-NIS: Navigating Semiconductor Process Corners with Neural Importance Sampling Poster

Hong Chul Nam · Chanwoo Park

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Planning Contextual Adaptive Experiments with Model Predictive Control Poster

Ethan Che · Jimmy Wang · Hongseok Namkoong

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Learning relevant contextual variables within Bayesian optimization Poster

Julien Martinelli · Ayush Bharti · Armi Tiihonen · Louis Filstroff · ST John · Sabina Sloman · Patrick Rinke · Samuel Kaski

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PINNACLE: PINN Adaptive ColLocation and Experimental points selection Poster

Gregory Kang Ruey Lau · Apivich Hemachandra · See-Kiong Ng · Bryan Kian Hsiang Low

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Accelerating Black-Box Molecular Property Optimization by Adaptively Learning Sparse Subspaces Poster

Farshud Sorourifar · Thomas Banker · Joel Paulson

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Ever Evolving Evaluator (EV3): Towards Flexible and Reliable Meta-Optimization for Knowledge Distillation Poster

Li Ding · Masrour Zoghi · Guy Tennenholtz · Maryam Karimzadehgan

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Provably-Convergent Bayesian Source Seeking for Multimodal Fields using Mobile Agents Poster

Vivek Mishra · Raul Astudillo · Peter Frazier · Fumin Zhang

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Compute-Efficient Active Learning Poster

Gábor Németh · Tamás Matuszka

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CircuitVAE: Efficient and Scalable Latent Circuit Optimization Poster

Jialin Song · Aidan Swope · Robert Kirby · Rajarshi Roy · Saad Godil · Jonathan Raiman · Bryan Catanzaro

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Unleashing the Autoconversion Rates Forecasting: Evidential Regression from Satellite Data Poster

Maria Carolina Novitasari · Johannes Quaas · Miguel Rodrigues

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Towards Scalable Identification of Brick Kilns from Satellite Imagery with Active Learning Poster

Aditi Agarwal · Suraj Jaiswal · Madhav Kanda · Dhruv Patel · Rishabh Mondal · Vannsh Jani · Zeel Bharatkumar Patel · Nipun Batra · Sarath Guttikunda

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Improved Bounds for Agnostic Active Learning of Single Index Models Poster

Aarshvi Gajjar · Xingyu Xu · Christopher Musco · Chinmay Hegde

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Practical Path-based Bayesian Optimization Poster

Jose Pablo Folch · James Odgers · Shiqiang Zhang · Robert Lee · Behrang Shafei · David Walz · Calvin Tsay · Mark van der Wilk · Ruth Misener

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Data-driven Prior Learning for Bayesian Optimisation Poster

Sigrid Passano Hellan · Christopher G Lucas · Nigel Goddard

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Model Robustness and Active Learning with Missing-Not-At-Random Outcomes Poster

Alan Mishler · Mohsen Ghassemi · Alec Koppel · Sumitra Ganesh

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Robust Fitted-Q-Evaluation and Iteration under Sequentially Exogenous Unobserved Confounders Poster

David Bruns-Smith · Angela Zhou

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BoChemian: Large Language Model Embeddings for Bayesian Optimization of Chemical Reactions Poster

Bojana Rankovic · Philippe Schwaller

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\textit{Less But Better}\\ Towards better \textit{AQ} Monitoring by learning \\ Inducing Points for Multi-Task Gaussian Processes Poster

Progyan Das · Mihir Agarwal

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ActSort: An active-learning accelerated cell sorting algorithm for large-scale calcium imaging datasets Poster

Hakki Akengin · Mehmet Aslihak · Yiqi Jiang · Christopher Miranda · Marta Pozo · Yang Li · Oscar Hernandez · Hakan Inan · Fatih Dinc · Mark Schnitzer

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Actively learning a Bayesian matrix fusion model with deep side information Poster

Yangyang Yu · Jordan Suchow

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Agile Modeling: From Concept to Classifier in Minutes Poster

Otilia Stretcu · Edward Vendrow · Kenji Hata · Krishnamurthy Viswanathan · Vittorio Ferrari · Sasan Tavakkol · Wenlei Zhou · Aditya Avinash · Enming Luo · Neil Alldrin · Mohammadhossein Bateni · Gabriel Berger · Andrew Bunner · Chun-Ta Lu · Javier Rey · Giulia DeSalvo · Ranjay Krishna · Ariel Fuxman

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Learning Models and Evaluating Policies with Offline Off-Policy Data under Partial Observability Poster

Shreyas Chaudhari · Philip Thomas · Bruno C. da Silva

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LabelBench: A Comprehensive Framework for Benchmarking Adaptive Label-Efficient Learning Poster

Jifan Zhang · Yifang Chen · Gregory Canal · Stephen Mussmann · Yinglun Zhu · Simon Du · Kevin Jamieson · Robert Nowak

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REDUCR: Robust Data Downsampling Using Class Priority Reweighting Poster

William Bankes · George Hughes · Ilija Bogunovic · Zi Wang

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Local Acquisition Function for Active Level Set Estimation Poster

Yuta Kokubun · Kota Matsui · Kentaro Kutsukake · Wataru Kumagai · Takafumi Kanamori

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Improving class and group imbalanced classification with uncertainty-based active learning Poster

Alexandru Tifrea · John Hill · Fanny Yang

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