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https://edubirdie.com/docs/amherst-college/math-211-multivariable-calculus/76125-math-211-differentiability-and-linear-approximation-for-functions-of-two-variables Differentiability and Linear Approximation for Functions | Amherst College - Edubirdie Math 211: Fall 2011 Differentiability and linear approximation for functions of two variables Suppose f is... Read more linear approximation amherst college differentiability functions edubirdie https://jmlr.org/papers/v23/21-0368.html Approximation and Optimization Theory for Linear Continuous-Time Recurrent Neural Networks optimization theory continuous time approximation https://ideas.repec.org/a/eee/dyncon/v105y2019icp21-43.html Log-linear approximation versus an exact solution at the ZLB in the New Keynesian model Downloadable (with restrictions)! How accurate is a log-linear approximation of the New Keynesian model when the nominal interest rate is bounded by zero? This... https://arxiv.org/abs/0804.1304 [0804.1304] Weak approximation of stochastic partial differential equations: the non linear case Abstract page for arXiv paper 0804.1304: Weak approximation of stochastic partial differential equations: the non linear case https://openreview.net/forum?id=6vDYsXn0Dl Linear Time Approximation Algorithm for Column Subset Selection with Local Search | OpenReview The Column Subset Selection (CSS) problem has been widely studied in dimensionality reduction and feature selection. The goal of the CSS problem is to output a... linear time approximation algorithm https://openreview.net/forum?id=NvaZn3uwzJ&referrer=%5Bthe%20profile%20of%20Jason%20D.%20Lee%5D(%2Fprofile%3Fid%3D~Jason_D._Lee1) Deployment Efficient Reward-Free Exploration with Linear Function Approximation | OpenReview We study deployment efficient reward-free exploration with linear function approximation, where the goal is to explore a linear Markov Decision Process (MDP)... linear function deployment efficient reward free https://arxiv.org/abs/2308.06153 [2308.06153] Non-linear WENO B-spline based approximation method Abstract page for arXiv paper 2308.06153: Non-linear WENO B-spline based approximation method non linear b spline 2308 06153 weno https://openreview.net/forum?id=h1WGiCxywu Misspecified $Q$-Learning with Sparse Linear Function Approximation: Tight Bounds on Approximation... The recent work by Dong and Yang (2023) showed for misspecified sparse linear bandits, one can obtain an $O\left(\epsilon\right)$-optimal policy using a... q learning linear function sparse https://arxiv.org/abs/2106.11960v1 [2106.11960v1] Variance-Aware Off-Policy Evaluation with Linear Function Approximation Abstract page for arXiv paper 2106.11960v1: Variance-Aware Off-Policy Evaluation with Linear Function Approximation policy evaluation linear function 2106 variance aware https://arxiv.org/abs/nlin/0208010 [nlin/0208010] Dynamo effect beyond the kinematic approximation: suppression of linear... Abstract page for arXiv paper nlin/0208010: Dynamo effect beyond the kinematic approximation: suppression of linear instabilities by non-linear feedback dynamo effect nlin beyond https://openreview.net/forum?id=vYZmTEDFoqP Provably Efficient Reinforcement Learning with Linear Function Approximation under Adaptivity... We study reinforcement learning (RL) with linear function approximation under the adaptivity constraint. We consider two popular limited adaptivity models: the... reinforcement learning linear function efficient approximation adaptivity https://www.nber.org/papers/w22784 Log-linear Approximation versus an Exact Solution at the ZLB in the New Keynesian Model | NBER Founded in 1920, the NBER is a private, non-profit, non-partisan organization dedicated to conducting economic research and to disseminating research findings... https://openreview.net/forum?id=9KEu1ZMeFF&referrer=%5Bthe%20profile%20of%20Francesco%20Orabona%5D(%2Fprofile%3Fid%3D~Francesco_Orabona1) A Finite-Time Analysis of TD Learning with Linear Function Approximation without Projections or... We investigate the finite-time convergence properties of Temporal Difference (TD) learning with linear function approximation, a cornerstone algorithm in the... https://arxiv.org/abs/2011.15048 [2011.15048] Optimal approximation to unitary quantum operators with linear optics Abstract page for arXiv paper 2011.15048: Optimal approximation to unitary quantum operators with linear optics 2011 optimal approximation https://openreview.net/forum?id=UP_GHHPw7rP Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation:... Offline reinforcement learning (RL) aims at learning an optimal strategy using a pre-collected dataset without further interactions with the environment. While... reinforcement learning linear function nearly minimax optimal