• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 208 matches

• 2021
• 
  Theresa Ziemke, Lucas Nunes Alegre, Ana L. C. Bazzan:
  Reinforcement learning vs. rule-based adaptive traffic signal control: A Fourier basis linear function approximation for traffic signal control. AI Commun. 34(1): 89-103 (2021)
• 
  Prashanth L. A., Nathaniel Korda, Rémi Munos:
  Concentration bounds for temporal difference learning with linear function approximation: the case of batch data and uniform sampling. Mach. Learn. 110(3): 559-618 (2021)
• 
  Hao Guo, Behrooz Makki, Mohamed-Slim Alouini, Tommy Svensson:
  A Semi-Linear Approximation of the First-Order Marcum Q-Function With Application to Predictor Antenna Systems. IEEE Open J. Commun. Soc. 2: 273-286 (2021)
• 
  Thinh T. Doan, Siva Theja Maguluri, Justin Romberg:
  Finite-Time Performance of Distributed Temporal-Difference Learning with Linear Function Approximation. SIAM J. Math. Data Sci. 3(1): 298-320 (2021)
• 
  Seok Young Kim, Chang Hyun Kim, Seon Wook Kim:
  Applying Piecewise Linear Approximation for DNN Non-Linear Activation Functions to Bfloat16 MACs. ICEIC 2021: 1-4
• 
  Tianhao Wang, Dongruo Zhou, Quanquan Gu:
  Provably Efficient Reinforcement Learning with Linear Function Approximation Under Adaptivity Constraints. CoRR abs/2101.02195 (2021)
• 
  Yue Wu, Dongruo Zhou, Quanquan Gu:
  Nearly Minimax Optimal Regret for Learning Infinite-horizon Average-reward MDPs with Linear Function Approximation. CoRR abs/2102.07301 (2021)
• 
  Zixiang Chen, Dongruo Zhou, Quanquan Gu:
  Almost Optimal Algorithms for Two-player Markov Games with Linear Function Approximation. CoRR abs/2102.07404 (2021)
• 
  Jiafan He, Dongruo Zhou, Quanquan Gu:
  Nearly Optimal Regret for Learning Adversarial MDPs with Linear Function Approximation. CoRR abs/2102.08940 (2021)
• 
  Lin Chen, Bruno Scherrer, Peter L. Bartlett:
  Infinite-Horizon Offline Reinforcement Learning with Linear Function Approximation: Curse of Dimensionality and Algorithm. CoRR abs/2103.09847 (2021)
• 
  Andrea Zanette, Ching-An Cheng, Alekh Agarwal:
  Cautiously Optimistic Policy Optimization and Exploration with Linear Function Approximation. CoRR abs/2103.12923 (2021)
• 
  Yue Wang, Shaofeng Zou, Yi Zhou:
  Finite-Sample Analysis for Two Time-scale Non-linear TDC with General Smooth Function Approximation. CoRR abs/2104.02836 (2021)
• 2020
• 
  He Zhang, Liang Zhang, David H. Mathews, Liang Huang:
  LinearPartition: linear-time approximation of RNA folding partition function and base-pairing probabilities. Bioinform. 36(Supplement-1): i258-i267 (2020)
• 
  Xinxin Gong, Bin Zhang:
  Fast computation of linear approximation over certain composition functions and applications to SNOW 2.0 and SNOW 3G. Des. Codes Cryptogr. 88(11): 2407-2431 (2020)
• 
  Huaqing Sun, Yuanyong Luo, Yajun Ha, Yinghuan Shi, Yang Gao, Qinghong Shen, Hongbing Pan:
  A Universal Method of Linear Approximation With Controllable Error for the Efficient Implementation of Transcendental Functions. IEEE Trans. Circuits Syst. I Regul. Pap. 67-I(1): 177-188 (2020)
• 
  Hongxi Dong, Manzhen Wang, Yuanyong Luo, Muhan Zheng, Mengyu An, Yajun Ha, Hongbing Pan:
  PLAC: Piecewise Linear Approximation Computation for All Nonlinear Unary Functions. IEEE Trans. Very Large Scale Integr. Syst. 28(9): 2014-2027 (2020)
• 
  Jun Sun, Gang Wang, Georgios B. Giannakis, Qinmin Yang, Zaiyue Yang:
  Finite-Time Analysis of Decentralized Temporal-Difference Learning with Linear Function Approximation. AISTATS 2020: 4485-4495
• 
  Chi Jin, Zhuoran Yang, Zhaoran Wang, Michael I. Jordan:
  Provably efficient reinforcement learning with linear function approximation. COLT 2020: 2137-2143
• 
  Theresa Ziemke, Lucas Nunes Alegre, Ana L. C. Bazzan:
  A Reinforcement Learning Approach with Fourier Basis Linear Function Approximation for Traffic Signal Control. ATT@ECAI 2020: 55-62
• 
  Yaqi Duan, Zeyu Jia, Mengdi Wang:
  Minimax-Optimal Off-Policy Evaluation with Linear Function Approximation. ICML 2020: 2701-2709
• 
  Gang Wang, Songtao Lu, Georgios B. Giannakis, Gerald Tesauro, Jian Sun:
  Decentralized TD Tracking with Linear Function Approximation and its Finite-Time Analysis. NeurIPS 2020
• 
  Diogo Carvalho, Francisco S. Melo, Pedro Santos:
  A new convergent variant of Q-learning with linear function approximation. NeurIPS 2020
• 
  Roshan Shariff, Csaba Szepesvári:
  Efficient Planning in Large MDPs with Weak Linear Function Approximation. NeurIPS 2020
• 
  Ruosong Wang, Simon S. Du, Lin F. Yang, Russ R. Salakhutdinov:
  On Reward-Free Reinforcement Learning with Linear Function Approximation. NeurIPS 2020
• 
  Yue Wang, Shaofeng Zou:
  Finite-sample Analysis of Greedy-GQ with Linear Function Approximation under Markovian Noise. UAI 2020: 11-20
• 
  Hao Guo, Behrooz Makki, Mohamed-Slim Alouini, Tommy Svensson:
  A Semi-Linear Approximation of the First-Order Marcum Q-function with Application to Predictor Antenna Systems. CoRR abs/2001.09264 (2020)
• 
  Tao Sun, Han Shen, Tianyi Chen, Dongsheng Li:
  Adaptive Temporal Difference Learning with Linear Function Approximation. CoRR abs/2002.08537 (2020)
• 
  Yaqi Duan, Mengdi Wang:
  Minimax-Optimal Off-Policy Evaluation with Linear Function Approximation. CoRR abs/2002.09516 (2020)
• 
  Gabriele Santin, Toni Karvonen, Bernard Haasdonk:
  Sampling based approximation of linear functionals in Reproducing Kernel Hilbert Spaces. CoRR abs/2004.00556 (2020)
• 
  Yue Wang, Shaofeng Zou:
  Finite-sample Analysis of Greedy-GQ with Linear Function Approximation under Markovian Noise. CoRR abs/2005.10175 (2020)

skipping 178 more matches