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Papers (including subtopics)

Linear Regression over Networks with Communication Guarantees L4DC 2021 Linear-Time Probabilistic Solution of Boundary Value Problems NeurIPS 2021 Local Convergence Analysis of Gradient Descent Ascent with Finite Timescale Separation ICLR 2021 Local Correlation Clustering with Asymmetric Classification Errors ICML 2021 Local Hyper-Flow Diffusion NeurIPS 2021 Localization, Convexity, and Star Aggregation NeurIPS 2021 Localized Simple Multiple Kernel K-Means ICCV 2021 Localizing Changes in High-Dimensional Regression Models AISTATS 2021 Locally differentially private estimation of functionals of discrete distributions NeurIPS 2021 LocalNewton: Reducing communication rounds for distributed learning UAI 2021 Local Search Algorithms for Rank-Constrained Convex Optimization ICLR 2021 Local Search for Diversified Top-k s-plex Search Problem (Student Abstract) AAAI 2021 Local SGD: Unified Theory and New Efficient Methods AISTATS 2021 Local Stochastic Gradient Descent Ascent: Convergence Analysis and Communication Efficiency AISTATS 2021 Logarithmic Regret from Sublinear Hints NeurIPS 2021 Logarithmic Regret in Feature-based Dynamic Pricing NeurIPS 2021 Logic Guided Genetic Algorithms (Student Abstract) AAAI 2021 Long-term, Short-term and Sudden Event: Trading Volume Movement Prediction with Graph-based Multi-view Modeling IJCAI 2021 Lossless Compression of Efficient Private Local Randomizers ICML 2021 Lower Bounds and Optimal Algorithms for Smooth and Strongly Convex Decentralized Optimization Over Time-Varying Networks NeurIPS 2021 Lower Bounds on Metropolized Sampling Methods for Well-Conditioned Distributions NeurIPS 2021 Low-Rank Extragradient Method for Nonsmooth and Low-Rank Matrix Optimization Problems NeurIPS 2021 Low-Rank Registration Based Manifolds for Convection-Dominated PDEs AAAI 2021 Low-Rank Sinkhorn Factorization ICML 2021 Low-Rank Tensor Completion by Approximating the Tensor Average Rank ICCV 2021