Mathematics

Efficient displacement convex optimization with particle gradient descent ICML 2023 Efficient Enumeration of Markov Equivalent DAGs AAAI 2023 Efficient fair PCA for fair representation learning AISTATS 2023 Efficient Graph Field Integrators Meet Point Clouds ICML 2023 Efficient k-NN Search with Cross-Encoders using Adaptive Multi-Round CUR Decomposition EMNLP 2023 Efficient preconditioned stochastic gradient descent for estimation in latent variable models ICML 2023 Efficient Robust Principal Component Analysis via Block Krylov Iteration and CUR Decomposition CVPR 2023 Efficient Second-Order Plane Adjustment CVPR 2023 Efficient Semiring-Weighted Earley Parsing ACL 2023 EigenTrajectory: Low-Rank Descriptors for Multi-Modal Trajectory Forecasting ICCV 2023 Energy-Based Sliced Wasserstein Distance NeurIPS 2023 Engineering an Efficient Approximate DNF-Counter IJCAI 2023 Enhanced Stable View Synthesis CVPR 2023 Entropic characterization of optimal rates for learning Gaussian mixtures COLT 2023 Equivariant Spatio-Temporal Attentive Graph Networks to Simulate Physical Dynamics NeurIPS 2023 Establishing Markov equivalence in cyclic directed graphs UAI 2023 Estimating Koopman operators with sketching to provably learn large scale dynamical systems NeurIPS 2023 Estimating Riemannian Metric with Noise-Contaminated Intrinsic Distance NeurIPS 2023 Estimating the Rate-Distortion Function by Wasserstein Gradient Descent NeurIPS 2023 Estimating Total Correlation with Mutual Information Estimators AISTATS 2023 Estimation Beyond Data Reweighting: Kernel Method of Moments ICML 2023 Evaluating Epistemic Logic Programs via Answer Set Programming with Quantifiers AAAI 2023 Evaluating Generative Networks Using Gaussian Mixtures of Image Features WACV 2023 Evaluating Instrument Validity using the Principle of Independent Mechanisms JMLR 2023 Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts NeurIPS 2023