Papers
572 papers found
Approximate Midpoint Policy Iteration for Linear Quadratic Control
Benjamin Gravell, Iman Shames, Tyler Summers
Approximate Distributionally Robust Nonlinear Optimization with Application to Model Predictive Control: A Functional Approach
Yassine Nemmour, Bernhard Schölkopf, Jia-Jie Zhu
Parameter-adaptive approximate MPC: Tuning neural-network controllers without retraining
Henrik Hose, Alexander Gräfe, Sebastian Trimpe
Probably approximately correct stability of allocations in uncertain coalitional games with private sampling
George Pantazis, Filiberto Fele, Filippo Fabiani et al.
Convolutional-recurrent neural networks approximate diffusion tractography from T1-weighted MRI and associated anatomical context
Leon Yichen Cai, Ho Hin Lee, Nancy Rose Newlin et al.
Approximate Bayesian Computation for an Explicit-Duration Hidden Markov Model of COVID-19 Hospital Trajectories
Gian Marco Visani, Alexandra Hope Lee, Cuong Nguyen et al.
Benchmarking Approximate Inference Methods for Neural Structured Prediction
Lifu Tu, Kevin Gimpel
Approximate Nearest Neighbour Extraction Techniques and Neural Networks for Suicide Risk Prediction in the CLPsych 2022 Shared Task
Hermenegildo Fabregat Marcos, Ander Cejudo, Juan Martinez-romo et al.
ALinFiK: Learning to Approximate Linearized Future Influence Kernel for Scalable Third-Party LLM Data Valuation
Yanzhou Pan, Huawei Lin, Yide Ran et al.
Gearbox: A Hierarchical Packet Scheduler for Approximate Weighted Fair Queuing
Peixuan Gao, Anthony Dalleggio, Yang Xu et al.
Dynamic Scheduling of Approximate Telemetry Queries
Chris Misa, Walt O'Connor, Ramakrishnan Durairajan et al.
Fast, Approximate Vector Queries on Very Large Unstructured Datasets
Zili Zhang, Chao Jin, Linpeng Tang et al.
Approximate Caching for Efficiently Serving Text-to-Image Diffusion Models
Shubham Agarwal, Subrata Mitra, Sarthak Chakraborty et al.
ASAP: Fast, Approximate Graph Pattern Mining at Scale
Anand Padmanabha Iyer, Zaoxing Liu, Xin Jin et al.
Correlated Equilibria for Approximate Variational
Inference in MRFs
Luis E. Ortiz, Boshen Wang, Ze Gong
Approximate Inference for Stochastic Planning in Factored Spaces
Zhennan Wu, Roni Khardon
On Stochastic Optimal Control and Reinforcement Learning by Approximate Inference
Konrad Rawlik, Marc Toussaint, Sethu Vijayakumar
Realtime Registration-Based Tracking via Approximate Nearest Neighbour Search
Travis Dick, Camilo Perez, Martin Jagersand et al.
Approximate Representations for Multi-Robot Control Policies that Maximize Mutual Information
Benjamin Charrow, Vijay Kumar, Nathan Michael
Approximate Bayesian Inference in Spatial Environments
Atanas Mirchev, Baris Kayalibay, Maximilian Soelch et al.
Traversing Supervisor Problem: An Approximately Optimal Approach to Multi-Robot Assistance
Tianchen Ji, Roy Dong, Katherine Driggs-Campbell
Coherence-based Approximate Derivatives via Web of Affine Spaces Optimization
Daniel Rakita, Chen Liang, Qian Wang