← Authors

Carlos Guestrin

44 papers · 2006–2025 · 10 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🐝 Cross-Pollinator (15) πŸƒ Academic Marathon (19) 🌈 Renaissance Researcher (8) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (10) πŸ—ΊοΈ Taxonomy Completionist (34) 🐣 Hot Topic Early Bird 🌟 Keyword Trendsetter Combo (12) 🌱 Topic Pioneer πŸ† Keyword Champion (3) πŸ“ˆ Trend Setter πŸ”₯ Unstoppable (8) πŸš€ Conference Pioneer πŸ—ƒοΈ Keyword Collector (112) ❓ The Questioner (4) πŸ’Ž Century Club (44)

Conferences

NIPS (16) AISTATS (7) ICML (7) ACL (3) JMLR (3) OSDI (3) NAACL (2) CVPR (1) ICLR (1) IJCAI (1)

Top co-authors

Sameer Singh (6) Marco Tulio Ribeiro (4) Tianqi Chen (4) Yucheng Low (3) Danny Bickson (3) Andreas Krause (3) Jonathan Huang (3) Arthur Gretton (3) Anton Chechetka (3) Tyler Johnson (2)

Research topics

Models (1) Probability (1)

Keywords

graphical model (7) submodular optimization (4) probabilistic inference (4) probabilistic modeling (3) neural network optimization (3) belief propagation (3) sensor placement (3) model evaluation (3) conditional random field (3) exact inference (3) sentiment analysis (3) markov chain monte carlo (2) l1 regularization (2) gaussian process (2) robust optimization (2) fourier analysis (2) mutual information (2) ensemble learning (2) model calibration (2) stochastic gradient descent (2)

Papers

Learning to (Learn at Test Time): RNNs with Expressive Hidden States ICML 2025
Benchmarking Distributional Alignment of Large Language Models NAACL 2025
Model Equality Testing: Which Model is this API Serving? ICLR 2025
Post-Hoc Reversal: Are We Selecting Models Prematurely? NIPS 2024
Beyond Confidence: Reliable Models Should Also Consider Atypicality NIPS 2023
AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback NIPS 2023
Learning Neural Network Subspaces ICML 2021
Beyond Accuracy: Behavioral Testing of NLP Models with Checklist (Extended Abstract) IJCAI 2021
AdaScale SGD: A User-Friendly Algorithm for Distributed Training ICML 2020
Beyond Accuracy: Behavioral Testing of NLP Models with CheckList ACL 2020
Adversarial Fisher Vectors for Unsupervised Representation Learning NIPS 2019
Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment ICML 2019
Are Red Roses Red? Evaluating Consistency of Question-Answering Models ACL 2019
TVM: An Automated End-to-End Optimizing Compiler for Deep Learning OSDI 2018
Learning to Optimize Tensor Programs NIPS 2018
Training Deep Models Faster with Robust, Approximate Importance Sampling NIPS 2018
Semantically Equivalent Adversarial Rules for Debugging NLP models ACL 2018
Scaling Submodular Maximization via Pruned Submodularity Graphs AISTATS 2017
StingyCD: Safely Avoiding Wasteful Updates in Coordinate Descent ICML 2017
Unified Methods for Exploiting Piecewise Linear Structure in Convex Optimization NIPS 2016
β€œWhy Should I Trust You?”: Explaining the Predictions of Any Classifier NAACL 2016
Efficient Second-Order Gradient Boosting for Conditional Random Fields AISTATS 2015
Blitz: A Principled Meta-Algorithm for Scaling Sparse Optimization ICML 2015
Learning Everything about Anything: Webly-Supervised Visual Concept Learning CVPR 2014
Stochastic Gradient Hamiltonian Monte Carlo ICML 2014
Divide-and-Conquer Learning by Anchoring a Conical Hull NIPS 2014
GraphChi: Large-Scale Graph Computation on Just a PC OSDI 2012
Sample Complexity of Composite Likelihood AISTATS 2012
PowerGraph: Distributed Graph-Parallel Computation on Natural Graphs OSDI 2012
Linear Submodular Bandits and their Application to Diversified Retrieval NIPS 2011
Parallel Gibbs Sampling: From Colored Fields to Thin Junction Trees AISTATS 2011
Kernel Belief Propagation AISTATS 2011
Nonparametric Tree Graphical Models AISTATS 2010
Focused Belief Propagation for Query-Specific Inference AISTATS 2010
Inference with Multivariate Heavy-Tails in Linear Models NIPS 2010
Evidence-Specific Structures for Rich Tractable CRFs NIPS 2010
Fourier Theoretic Probabilistic Inference over Permutations JMLR 2009
Riffled Independence for Ranked Data NIPS 2009
Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies JMLR 2008
Robust Submodular Observation Selection JMLR 2008
Efficient Principled Learning of Thin Junction Trees NIPS 2007
Efficient Inference for Distributions on Permutations NIPS 2007
Selecting Observations against Adversarial Objectives NIPS 2007
Distributed Inference in Dynamical Systems NIPS 2006