Non Parametric Learning

Nonparametric learning focuses on developing machine learning models that make minimal assumptions about the underlying data distribution, enabling the modeling of complex, high-dimensional relationships without restrictive parametric constraints. Current research emphasizes efficient algorithms like kernel methods (including kernel ridge regression and RKHS-based approaches), nearest neighbor techniques (enhanced with information-theoretic principles), and Bayesian methods (incorporating flexible nonparametric priors for improved transfer learning). These advancements are improving the accuracy, interpretability, and robustness of models across diverse applications, including regression, classification, anomaly detection, and causal inference, particularly in scenarios with limited data or significant distribution shifts.

Papers

October 23, 2024

A Kernel Perspective on Distillation-based Collaborative Learning
Sejun Park, Kihun Hong, Ganguk Hwang
Knowledge Distillation Kernel Regression Kernel Based Non Parametric Learning Algorithm Distillation Adaptive Knowledge Distillation

October 17, 2024

Ab initio nonparametric variable selection for scalable Symbolic Regression with large $p$
Shengbin Ye, Meng Li
High Dimensional Novel Regression Symbolic Regression Variable Selection Nonparametric Regression Ab Initio Non Parametric Learning Symbolic Approach

May 17, 2024

Nonparametric Teaching of Implicit Neural Representations
Chen Zhang, Steven Tin Sui Luo, Jason Chun Lok Li, Yik-Chung Wu, Ngai Wong
Implicit Neural Representation Multi Layer Perceptron Non Parametric Learning Nonparametric Teaching

April 25, 2024

mlr3summary: Concise and interpretable summaries for machine learning models
Susanne Dandl, Marc Becker, Bernd Bischl, Giuseppe Casalicchio, Ludwig Bothmann
Machine Learning Model Structured Output R Package Aggregation Function Non Parametric Learning

March 12, 2024

Enhancing Transfer Learning with Flexible Nonparametric Posterior Sampling
Hyungi Lee, Giung Nam, Edwin Fong, Juho Lee
Transfer Learning Posterior Sampling Prior Distribution Non Parametric Learning Caution Aware Transfer

December 11, 2023

Uncertainty quantification in automated valuation models with locally weighted conformal prediction
Anders Hjort, Gudmund Horn Hermansen, Johan Pensar, Jonathan P. Williams
Uncertainty Quantification Conformal Prediction Prediction Uncertainty Valuation Model Non Parametric Learning Confidence Set

November 17, 2023

Surprisal Driven $k$-NN for Robust and Interpretable Nonparametric Learning
Amartya Banerjee, Christopher J. Hazard, Jacob Beel, Cade Mack, Jack Xia, Michael Resnick, Will Goddin
Machine Learning Robust Version Nearest Neighbor Non Parametric Learning Conditional Entropy Interpretable Learning Surprisal Driven

July 24, 2023

Nonparametric Linear Feature Learning in Regression Through Regularisation
Bertille Follain, Francis Bach
Representation Learning Novel Regression Regularization Model High Dimensional Data Non Parametric Learning Linear Region Dimensional Subspace

June 5, 2023

Learning nonparametric latent causal graphs with unknown interventions
Yibo Jiang, Bryon Aragam
Latent Space Latent Causal Latent Structure Parametric Model Non Parametric Learning Unknown Intervention

May 24, 2023

Non-Parametric Learning of Stochastic Differential Equations with Non-asymptotic Fast Rates of Convergence
Riccardo Bonalli, Alessandro Rudi
Early Stage Convergence Learning Rate Stochastic Differential Equation Non Asymptotic Fokker Planck Equation Non Parametric Learning Diffusion Coefficient

May 5, 2023

Decentralized diffusion-based learning under non-parametric limited prior knowledge
Paweł Wachel, Krzysztof Kowalczyk, Cristian R. Rojas
Decentralized Learning Prior Model Non Parametric Learning Diffusion Network Decentralized Network Neighboring Node

April 6, 2023

Multi-Linear Kernel Regression and Imputation in Data Manifolds
Duc Thien Nguyen, Konstantinos Slavakis
Kernel Hilbert Space Kernel Regression Deep Image Prior Knowledge Enhanced Conditional Imputation Data Manifold Dynamic Magnetic Resonance Non Parametric Learning

March 9, 2023

Fast kernel methods for Data Quality Monitoring as a goodness-of-fit test
Gaia Grosso, Nicolò Lai, Marco Letizia, Jacopo Pazzini, Marco Rando, Lorenzo Rosasco, Andrea Wulzer, Marco Zanetti
Machine Learning Approach Kernel Method Data Quality Non Parametric Learning Particle Detector Goodness of Fit Fast Kernel

December 2, 2022

Clustering through Feature Space Sequence Discovery and Analysis
Shi Guobin
General Analysis Data Science Non Parametric Learning Sequence Recognition Dimensional Data Pattern

October 5, 2022

Nonparametric Decoding for Generative Retrieval
Hyunji Lee, Jaeyoung Kim, Hoyeon Chang, Hanseok Oh, Sohee Yang, Vlad Karpukhin, Yi Lu, Minjoon Seo
Generative Retrieval Non Parametric Learning

August 24, 2022

Metric Effects based on Fluctuations in values of k in Nearest Neighbor Regressor
Abhishek Gupta, Raunak Joshi, Nandan Kanvinde, Pinky Gerela, Ronald Melwin Laban
Nearest Neighbor Metric Library Regression Model Policy Value K Content Non Parametric Learning Fluctuation Analysis

June 30, 2022

Learning nonparametric ordinary differential equations from noisy data
Kamel Lahouel, Michael Wells, Victor Rielly, Ethan Lew, David Lovitz, Bruno M. Jedynak
Machine Learning Strong Generalization Noisy Data Reproducing Kernel Hilbert Space Ordinary Differential Equation Non Parametric Learning

June 23, 2022

Few-Shot Non-Parametric Learning with Deep Latent Variable Model
Zhiying Jiang, Yiqin Dai, Ji Xin, Ming Li, Jimmy Lin
Generative Model Latent Variable Model Unsupervised Manner Distance Metric Non Parametric Learning Classification Application

May 23, 2022

Nonparametric learning of kernels in nonlocal operators
Fei Lu, Qingci An, Yue Yu
Ill Posed Inverse Problem Small Kernel Kernel Based Non Parametric Learning Adaptive RKHS Tikhonov Regularization Nonlocal Operator

March 24, 2022

Non-Parametric Stochastic Policy Gradient with Strategic Retreat for Non-Stationary Environment
Apan Dastider, Mingjie Lin
Deep Deterministic Policy Gradient Non Stationary Environment Non Parametric Learning Deterministic Policy Gradient Stochastic Policy Gradient Strategic Maneuver