Mathematics

On the Expected Size of Conformal Prediction Sets AISTATS 2024 On the Expressive Power of Tree-Structured Probabilistic Circuits NeurIPS 2024 On the Expressivity of Recurrent Neural Cascades AAAI 2024 On the Lasso for Graphical Continuous Lyapunov Models CLeaR 2024 On the Limitations of Fractal Dimension as a Measure of Generalization NeurIPS 2024 On the Nyström Approximation for Preconditioning in Kernel Machines AISTATS 2024 On the Optimality of Gaussian Kernel Based Nonparametric Tests against Smooth Alternatives JMLR 2024 On the Parameter Identifiability of Partially Observed Linear Causal Models NeurIPS 2024 On the Robustness of Spectral Algorithms for Semirandom Stochastic Block Models NeurIPS 2024 On The Statistical Complexity of Offline Decision-Making ICML 2024 On the Structural Hardness of Answer Set Programming: Can Structure Efficiently Confine the Power of Disjunctions? AAAI 2024 On the Unlikelihood of D-Separation PGM 2024 On Unbiased Estimation for Partially Observed Diffusions JMLR 2024 Open problem: Convergence of single-timescale mean-field Langevin descent-ascent for two-player zero-sum games COLT 2024 Open problem: Direct Sums in Learning Theory COLT 2024 Open Problem: Tight Characterization of Instance-Optimal Identity Testing COLT 2024 Optimal Algorithms for Augmented Testing of Discrete Distributions NeurIPS 2024 Optimal deep learning of holomorphic operators between Banach spaces NeurIPS 2024 Optimal Differentially Private Model Training with Public Data ICML 2024 Optimal estimation of Gaussian (poly)trees AISTATS 2024 Optimal Extended Formulations from Optimal Dynamic Programming Algorithms IJCAI 2024 Optimal Quasi-clique: Hardness, Equivalence with Densest-k-Subgraph, and Quasi-partitioned Community Mining AAAI 2024 Optimal Scaling for the Proximal Langevin Algorithm in High Dimensions JMLR 2024 Optimal score estimation via empirical Bayes smoothing COLT 2024 Optimal Sketching for Residual Error Estimation for Matrix and Vector Norms ICLR 2024