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07/13/2023
Generating Benchmarks for Factuality Evaluation of Language Models
Before deploying a language model (LM) within a given domain, it is impo...
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06/07/2023
Loss Functions for Behavioral Game Theory
Behavioral game theorists all use experimental data to evaluate predicti...
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01/31/2023
In-Context Retrieval-Augmented Language Models
Retrieval-Augmented Language Modeling (RALM) methods, that condition a l...
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12/21/2022
Parallel Context Windows Improve In-Context Learning of Large Language Models
For applications that require processing large amounts of text at infere...
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11/22/2022
Monte Carlo Forest Search: UNSAT Solver Synthesis via Reinforcement learning
We introduce Monte Carlo Forest Search (MCFS), an offline algorithm for ...
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10/31/2022
Artificial Intelligence and Life in 2030: The One Hundred Year Study on Artificial Intelligence
In September 2016, Stanford's "One Hundred Year Study on Artificial Inte...
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09/02/2022
Better Peer Grading through Bayesian Inference
Peer grading systems aggregate noisy reports from multiple students to a...
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05/25/2022
Formalizing Preferences Over Runtime Distributions
When trying to solve a computational problem we are often faced with a c...
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05/01/2022
MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning
Huge language models (LMs) have ushered in a new era for AI, serving as ...
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02/24/2022
Matching Papers and Reviewers at Large Conferences
This paper studies a novel reviewer-paper matching approach that was rec...
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07/01/2021
The Spotlight: A General Method for Discovering Systematic Errors in Deep Learning Models
Supervised learning models often make systematic errors on rare subsets ...
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06/18/2021
The Perils of Learning Before Optimizing
Formulating real-world optimization problems often begins with making pr...
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01/18/2021
Mechanical TA 2: A System for Peer Grading with TA Support
Mechanical TA 2 (MTA2) is an open source web-based peer grading applicat...
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12/01/2020
Dynamic Weighted Matching with Heterogeneous Arrival and Departure Rates
We study a dynamic non-bipartite matching problem. There is a fixed set ...
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11/02/2020
Exemplar Guided Active Learning
We consider the problem of wisely using a limited budget to label a smal...
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10/05/2020
PMI-Masking: Principled masking of correlated spans
Masking tokens uniformly at random constitutes a common flaw in the pret...
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06/19/2020
Valid Causal Inference with (Some) Invalid Instruments
Instrumental variable methods provide a powerful approach to estimating ...
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06/08/2020
Learning under Invariable Bayesian Safety
A recent body of work addresses safety constraints in explore-and-exploi...
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03/21/2020
Smarter Parking: Using AI to Identify Parking Inefficiencies in Vancouver
On-street parking is convenient, but has many disadvantages: on-street s...
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06/13/2019
Report-Sensitive Spot-Checking in Peer-Grading Systems
Peer grading systems make large courses more scalable, provide students ...
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05/16/2019
Fiduciary Bandits
Recommendation systems often face exploration-exploitation tradeoffs: th...
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02/14/2019
Procrastinating with Confidence: Near-Optimal, Anytime, Adaptive Algorithm Configuration
Algorithm configuration methods optimize the performance of a parameteri...
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12/30/2018
A Formal Separation Between Strategic and Nonstrategic Behavior
It is common to make a distinction between `strategic' behavior and othe...
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12/30/2018
Formalizing the Boundary Between Strategic and Nonstrategic Reasoning
Research in multiagent systems often does not draw a clear distinction b...
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03/07/2018
Deep Models of Interactions Across Sets
We use deep learning to model interactions across two or more sets of ob...
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06/11/2017
Deep Optimization for Spectrum Repacking
Over 13 months in 2016-17 the FCC conducted an "incentive auction" to re...
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03/30/2017
Efficient Benchmarking of Algorithm Configuration Procedures via Model-Based Surrogates
The optimization of algorithm (hyper-)parameters is crucial for achievin...
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12/30/2016
Counterfactual Prediction with Deep Instrumental Variables Networks
We are in the middle of a remarkable rise in the use and capability of a...
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06/08/2015
ASlib: A Benchmark Library for Algorithm Selection
The task of algorithm selection involves choosing an algorithm from a se...
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05/05/2015
The Configurable SAT Solver Challenge (CSSC)
It is well known that different solution strategies work well for differ...
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08/04/2014
Computational Analysis of Perfect-Information Position Auctions
After experimentation with other designs, the major search engines conve...
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01/15/2014
ParamILS: An Automatic Algorithm Configuration Framework
The identification of performance-optimizing parameter settings is an im...
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10/07/2013
Bayesian Optimization With Censored Response Data
Bayesian optimization (BO) aims to minimize a given blackbox function us...
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11/05/2012
Algorithm Runtime Prediction: Methods & Evaluation
Perhaps surprisingly, it is possible to predict how long an algorithm wi...
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05/09/2012
Temporal Action-Graph Games: A New Representation for Dynamic Games
In this paper we introduce temporal action graph games (TAGGs), a novel ...
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10/31/2011