Papers
572 papers found
Approximate State Abstraction for Markov Games
Hiroki Ishibashi, Kenshi Abe, Atsushi Iwasaki
Approximated Variational Bayesian Inverse Reinforcement Learning for Large Language Model Alignment
Yuang Cai, Yuyu Yuan, Jinsheng Shi et al.
Formally Verified Approximate Policy Iteration
Maximilian Schäffeler, Mohammad Abdulaziz
How Well Does First-Token Entropy Approximate Word Entropy as a Psycholinguistic Predictor?
Christian Clark, Byung-Doh Oh, William Schuler
Extensive Error Analysis and a Learning-Based Evaluation of Medical Entity Recognition Systems to Approximate User Experience
Isar Nejadgholi, Kathleen C. Fraser, Berry de Bruijn
Corpus Poisoning via Approximate Greedy Gradient Descent
Jinyan Su, Preslav Nakov, Claire Cardie
A Study of Approximate Inference in Probabilistic Relational Models
Fabian Kaelin, Doina Precup
Approximate Model Selection for Large Scale LSSVM
Lizhong Ding, Shizhong Liao
Gradient-based Training of Slow Feature Analysis by Differentiable Approximate Whitening
Merlin Schüler, Hlynur Davíð Hlynsson, Laurenz Wiskott
Approximate parameter inference in a stochastic reaction-diffusion model
Andreas Ruttor, Manfred Opper
Guarantees for Approximate Incremental SVMs
Nicolas Usunier, Antoine Bordes, Léon Bottou
Switch-Reset Models : Exact and Approximate Inference
Chris Bracegirdle, David Barber
Approximate inference for the loss-calibrated Bayesian
Simon Lacoste–Julien, Ferenc Huszár, Zoubin Ghahramani
Fast Convergent Algorithms for Expectation Propagation Approximate Bayesian Inference
Matthias Seeger, Hannes Nickisch
Empirical Risk Minimization of Graphical Model Parameters Given Approximate Inference, Decoding, and Model Structure
Veselin Stoyanov, Alexander Ropson, Jason Eisner
Approximate Inference by Intersecting Semidefinite Bound and Local Polytope
Jian Peng, Tamir Hazan, Nathan Srebro et al.
Approximate Inference in Additive Factorial HMMs with Application to Energy Disaggregation
J. Zico Kolter, Tommi Jaakkola
Approximate Slice Sampling for Bayesian Posterior Inference
Christopher DuBois, Anoop Korattikara, Max Welling et al.
High-Dimensional Density Ratio Estimation with Extensions to Approximate Likelihood Computation
Rafael Izbicki, Ann Lee, Chad Schafer
On Approximate Non-submodular Minimization via Tree-Structured Supermodularity
Yoshinobu Kawahara, Rishabh Iyer, Jeffrey Bilmes
K2-ABC: Approximate Bayesian Computation with Kernel Embeddings
Mijung Park, Wittawat Jitkrittum, Dino Sejdinovic
Probabilistic Approximate Least-Squares
Simon Bartels, Philipp Hennig