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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
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Abstract

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Schedule

Timezone: America/Los_Angeles
6:30 AM
Opening Remarks
8:00 AM
Coffee Break
1:10 PM
Coffee Break
3:00 PM
Poster Session
Model-Free Preference Elicitation
Carlos Martin ⋅ Craig Boutilier ⋅ Ofer Meshi
Active Learning for Iterative Offline Reinforcement Learning
Lan Zhang ⋅ Luigi Franco Tedesco ⋅ Pankaj Rajak ⋅ Youcef Zemmouri ⋅ Hakan Brunzell
Anytime-Valid Inference in Adaptive Experiments
Thomas Cook ⋅ Alan Mishler ⋅ Aaditya Ramdas
Pure Exploration under Mediators’ Feedback
Riccardo Poiani ⋅ Alberto Maria Metelli ⋅ Marcello Restelli
DISTRIBUTIONALLY ROBUST MODEL-BASED REINFORCEMENT LEARNING WITH LARGE STATE SPACES
Shyam Sundhar Ramesh ⋅ Pier Giuseppe Sessa ⋅ Yifan Hu ⋅ Andreas Krause ⋅ Ilija Bogunovic
Sustainable Concrete via Bayesian Optimization
Sebastian Ament ⋅ Andrew Witte ⋅ Nishant Garg ⋅ Julius Kusuma
Exploratory Training: When Annotators Learn About Data
Rajesh Shrestha ⋅ Omeed Habibelahian ⋅ Arash Termehchy ⋅ Paolo Papotti
Graph Neural Bayesian Optimization for Virtual Screening
Miles Wang-Henderson ⋅ Bartu Soyuer ⋅ Parnian Kassraie ⋅ Andreas Krause ⋅ Ilija Bogunovic
Hessian-Free Laplace in Bayesian Deep Learning
James McInerney ⋅ Nathan Kallus
On Complex Network Dynamics of an In-Vitro Neuronal System during Rest and Gameplay
Moein Khajehnejad ⋅ Forough Habibollahi ⋅ Alon Loeffler ⋅ Brett J. Kagan ⋅ Adeel Razi
Human-in-the-Loop Out-of-Distribution Detection with False Positive Rate Control
Harit Vishwakarma ⋅ Heguang Lin ⋅ Ramya Korlakai Vinayak
Cross-Entropy Estimators for Sequential Experiment Design with Reinforcement Learning
Tom Blau ⋅ Iadine Chades ⋅ Amir Dezfouli ⋅ Daniel Steinberg ⋅ Edwin Bonilla
Correlated Trajectory Uncertainty for Adaptive Sequential Decision Making
Ian Char ⋅ Youngseog Chung ⋅ Rohan Shah ⋅ Willie Neiswanger ⋅ Jeff Schneider
Efficient and scalable reinforcement learning via Hypermodel
Yingru Li ⋅ Jiawei Xu ⋅ Zhi-Quan Luo
ALAS: Active Learning for Autoconversion Rates Prediction from Satellite Data
Maria Carolina Novitasari ⋅ Johannes Quaas ⋅ Miguel Rodrigues
Active Testing of Binary Classification Model Using Level Set Estimation
Takuma Ochiai ⋅ Keiichiro Seno ⋅ Kota Matsui ⋅ Satoshi Hara
Nonparametric Discrete Choice Experiments with Machine Learning Guided Adaptive Design
Mingzhang Yin ⋅ Ruijiang Gao ⋅ Weiran Lin ⋅ Steven Shugan
Active Learning Policies for Solving Inverse Problems
Tim Bakker ⋅ Thomas Hehn ⋅ Tribhuvanesh Orekondy ⋅ Arash Behboodi ⋅ Fabio Valerio Massoli
ExPT: Scaling Foundation Models for Experimental Design via Synthetic Pretraining
Tung Nguyen ⋅ Sudhanshu Agrawal ⋅ Aditya Grover
AutODEx: Automated Optimal Design of Experiments Platform with Data- and Time-Efficient Multi-Objective Optimization
Yunsheng Tian ⋅ Pavle Konakovic ⋅ Beichen Li ⋅ Ane Zuniga ⋅ Michael Foshey ⋅ Timothy Erps ⋅ Wojciech Matusik ⋅ Mina Konakovic Lukovic
Understanding Threshold-based Auto-labeling: The Good, the Bad, and the Terra Incognita
Harit Vishwakarma ⋅ Heguang Lin ⋅ Frederic Sala ⋅ Ramya Korlakai Vinayak
Anytime Model Selection in Linear Bandits
Parnian Kassraie ⋅ Nicolas Emmenegger ⋅ Andreas Krause ⋅ Aldo Pacchiano
Multi-Fidelity Active Learning with GFlowNets
Alex Hernandez-Garcia ⋅ Nikita Saxena ⋅ Moksh Jain ⋅ Chenghao Liu ⋅ Yoshua Bengio
Learning in Clinical Trial Settings
Zoe Fowler ⋅ Kiran Kokilepersaud ⋅ Mohit Prabhushankar ⋅ Ghassan AlRegib
Preferential Heteroscedastic Bayesian Optimization with Informative Noise Priors
Marshal Sinaga ⋅ Julien Martinelli ⋅ Samuel Kaski
Optimistic Games for Combinatorial Bayesian Optimization with Applications to Protein Design
Melis Ilayda Bal ⋅ Pier Giuseppe Sessa ⋅ Mojmir Mutny ⋅ Andreas Krause
Planning Contextual Adaptive Experiments with Model Predictive Control
Ethan Che ⋅ Jimmy Wang ⋅ Hongseok Namkoong
Learning relevant contextual variables within Bayesian optimization
Julien Martinelli ⋅ Ayush Bharti ⋅ Armi Tiihonen ⋅ Louis Filstroff ⋅ ST John ⋅ Sabina Sloman ⋅ Patrick Rinke ⋅ Samuel Kaski
PINNACLE: PINN Adaptive ColLocation and Experimental points selection
Gregory Kang Ruey Lau ⋅ Apivich Hemachandra ⋅ See-Kiong Ng ⋅ Bryan Kian Hsiang Low
Ever Evolving Evaluator (EV3): Towards Flexible and Reliable Meta-Optimization for Knowledge Distillation
Li Ding ⋅ Masrour Zoghi ⋅ Guy Tennenholtz ⋅ Maryam Karimzadehgan
Provably-Convergent Bayesian Source Seeking for Multimodal Fields using Mobile Agents
Vivek Mishra ⋅ Raul Astudillo ⋅ Peter Frazier ⋅ Fumin Zhang
Compute-Efficient Active Learning
Gábor Németh ⋅ Tamás Matuszka
CircuitVAE: Efficient and Scalable Latent Circuit Optimization
Jialin Song ⋅ Aidan Swope ⋅ Robert Kirby ⋅ Rajarshi Roy ⋅ Saad Godil ⋅ Jonathan Raiman ⋅ Bryan Catanzaro
Unleashing the Autoconversion Rates Forecasting: Evidential Regression from Satellite Data
Maria Carolina Novitasari ⋅ Johannes Quaas ⋅ Miguel Rodrigues
Towards Scalable Identification of Brick Kilns from Satellite Imagery with Active Learning
Aditi Agarwal ⋅ Suraj Jaiswal ⋅ Madhav Kanda ⋅ Dhruv Patel ⋅ Rishabh Mondal ⋅ Vannsh Jani ⋅ Zeel Bharatkumar Patel ⋅ Nipun Batra ⋅ Sarath Guttikunda
Improved Bounds for Agnostic Active Learning of Single Index Models
Aarshvi Gajjar ⋅ Xingyu Xu ⋅ Christopher Musco ⋅ Chinmay Hegde
Practical Path-based Bayesian Optimization
Jose Pablo Folch ⋅ James Odgers ⋅ Shiqiang Zhang ⋅ Robert Lee ⋅ Behrang Shafei ⋅ David Walz ⋅ Calvin Tsay ⋅ Mark van der Wilk ⋅ Ruth Misener
Data-driven Prior Learning for Bayesian Optimisation
Sigrid Passano Hellan ⋅ Christopher G Lucas ⋅ Nigel Goddard
Model Robustness and Active Learning with Missing-Not-At-Random Outcomes
Alan Mishler ⋅ Mohsen Ghassemi ⋅ Alec Koppel ⋅ Sumitra Ganesh
ActSort: An active-learning accelerated cell sorting algorithm for large-scale calcium imaging datasets
Hakki Akengin ⋅ Mehmet Aslihak ⋅ Yiqi Jiang ⋅ Christopher Miranda ⋅ Marta Pozo ⋅ Yang Li ⋅ Oscar Hernandez ⋅ Hakan Inan ⋅ Fatih Dinc ⋅ Mark Schnitzer
Agile Modeling: From Concept to Classifier in Minutes
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
LabelBench: A Comprehensive Framework for Benchmarking Adaptive Label-Efficient Learning
Jifan Zhang ⋅ Yifang Chen ⋅ Gregory Canal ⋅ Stephen Mussmann ⋅ Yinglun Zhu ⋅ Simon Du ⋅ Kevin Jamieson ⋅ Robert Nowak
REDUCR: Robust Data Downsampling Using Class Priority Reweighting
William Bankes ⋅ George Hughes ⋅ Ilija Bogunovic ⋅ Zi Wang
Local Acquisition Function for Active Level Set Estimation
Yuta Kokubun ⋅ Kota Matsui ⋅ Kentaro Kutsukake ⋅ Wataru Kumagai ⋅ Takafumi Kanamori