1 citations · 1 across the 7 of their papers we have counts for
11 papers
Intrinsic Associative Memory on Riemannian Manifolds: Curvature, Capacity, and Emergent Modes
Krishnakumar Balasubramanian, Zhaoyang Shi
Geometry does more than constrain an associative memory: curvature determines what it remembers and which states it creates. We develop intrinsic dense associative memories on Riem…
Graph Memory: Spectral Associative Memory via Dirichlet Energy
Zhaoyang Shi
Dense associative memories have traditionally focused on storing and retrieving vector-valued patterns. Many modern machine learning problems, however, are naturally graph-structur…
Population-Level Generative Modeling for Ranking Data
Zhaoyang Shi
Ranking data arise in scientific and machine learning applications, including recommendation systems, information retrieval, voting, marketing, and AI preference ranking from human…
Optimal Demixing of Nonparametric Densities
Jianqing Fan, Zheng Tracy Ke, Zhaoyang Shi
Motivated by applications in statistics and machine learning, we consider a problem of unmixing convex combinations of nonparametric densities. Suppose we observe groups of sam…
Dense Associative Memory with Epanechnikov Energy
Benjamin Hoover, Zhaoyang Shi, Krishnakumar Balasubramanian +2
We propose a novel energy function for Dense Associative Memory (DenseAM) networks, the log-sum-ReLU (LSR), inspired by optimal kernel density estimation. Unlike the common log-sum…
LOD: Latent Objective Discovery in Heterogeneous Multi-Agent Reinforcement Learning
Ke Sun, Zhaoyang Shi
In multi-agent reinforcement learning (MARL) settings, agents are often heterogeneous with diverse intrinsic utility functions. In this study, we introduce Latent Objective Discove…
Gaussian and Bootstrap Approximation for Matching-based Average Treatment Effect Estimators
Zhaoyang Shi, Chinmoy Bhattacharjee, Krishnakumar Balasubramanian +1
We establish Gaussian approximation bounds for covariate and rank-matching-based Average Treatment Effect (ATE) estimators. By analyzing these estimators through the lens of stabil…
Multivariate Gaussian Approximation for Random Forest via Region-based Stabilization
Zhaoyang Shi, Chinmoy Bhattacharjee, Krishnakumar Balasubramanian +1
We derive Gaussian approximation bounds for -Potential Nearest Neighbor (-PNN) based random forest predictions based on a set of training points given by a Poisson process un…
Nonsmooth Nonparametric Regression via Fractional Laplacian Eigenmaps
Zhaoyang Shi, Krishnakumar Balasubramanian, Wolfgang Polonik
We develop nonparametric regression methods for the case when the true regression function is not necessarily smooth. More specifically, our approach is using the fractional Laplac…
Adaptive and non-adaptive minimax rates for weighted Laplacian-eigenmap based nonparametric regression
Zhaoyang Shi, Krishnakumar Balasubramanian, Wolfgang Polonik
We show both adaptive and non-adaptive minimax rates of convergence for a family of weighted Laplacian-Eigenmap based nonparametric regression methods, when the true regression fun…
A Flexible Approach for Normal Approximation of Geometric and Topological Statistics
Zhaoyang Shi, Krishnakumar Balasubramanian, Wolfgang Polonik
We derive normal approximation results for a class of stabilizing functionals of binomial or Poisson point process, that are not necessarily expressible as sums of certain score fu…