Cover Image

Probabilistic Hash Embeddings for Online Learning of Categorical Features

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Aodong, Sankararaman, Abishek, Narayanaswamy, Balakrishnan
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Competing Bandits in Decentralized Contextual Matching Markets
by: Parikh, Satush, et al.
Published: (2024)

AgentSM: Semantic Memory for Agentic Text-to-SQL
by: Biswal, Asim, et al.
Published: (2026)

The Gossiping Insert-Eliminate Algorithm for Multi-Agent Bandits
by: Chawla, Ronshee, et al.
Published: (2020)

ODIN: A NL2SQL Recommender to Handle Schema Ambiguity
by: Vaidya, Kapil, et al.
Published: (2025)

Controllable Discovery of Intents: Incremental Deep Clustering Using Semi-Supervised Contrastive Learning
by: Rawat, Mrinal, et al.
Published: (2024)

SynLexLM: Scaling Legal LLMs with Synthetic Data and Curriculum Learning
by: Upadhyay, Ojasw, et al.
Published: (2025)

Multi-task Online Learning for Probabilistic Load Forecasting
by: Zaballa, Onintze, et al.
Published: (2025)

Probabilistic Load Forecasting Based on Adaptive Online Learning
by: Álvarez, Verónica, et al.
Published: (2020)

CAVIAR: Categorical-Variable Embeddings for Accurate and Robust Inference
by: Mukherjee, Anirban, et al.
Published: (2024)

Improving DBMS Scheduling Decisions with Fine-grained Performance Prediction on Concurrent Queries -- Extended
by: Wu, Ziniu, et al.
Published: (2025)

Closing the gap on tabular data with Fourier and Implicit Categorical Features
by: Dragoi, Marius, et al.
Published: (2026)

Model Selection of Anomaly Detectors in the Absence of Labeled Validation Data
by: Fung, Clement, et al.
Published: (2023)

Codebook-Centric Deep Hashing: End-to-End Joint Learning of Semantic Hash Centers and Neural Hash Function
by: Yin, Shuo, et al.
Published: (2025)

dotears: Scalable, consistent DAG estimation using observational and interventional data
by: Xue, Albert, et al.
Published: (2023)

Multi-Probe Zero Collision Hash (MPZCH): Mitigating Embedding Collisions and Enhancing Model Freshness in Large-Scale Recommenders
by: Zhao, Ziliang, et al.
Published: (2026)

Hashing-Baseline: Rethinking Hashing in the Age of Pretrained Models
by: Moummad, Ilyass, et al.
Published: (2025)

Robustness of Practical Perceptual Hashing Algorithms to Hash-Evasion and Hash-Inversion Attacks
by: Madden, Jordan, et al.
Published: (2024)

Conformal Online Learning of Deep Koopman Linear Embeddings
by: Gao, Ben, et al.
Published: (2025)

Posterior Sampling of Probabilistic Word Embeddings
by: Yrjänäinen, Väinö, et al.
Published: (2025)

Hermite-NGP: Gradient-Augmented Hash Encoding for Learning PDEs
by: He, Jinjin, et al.
Published: (2026)

CACTI: Leveraging Copy Masking and Contextual Information to Improve Tabular Data Imputation
by: Gorla, Aditya, et al.
Published: (2025)

Murmur2Vec: A Hashing Based Solution For Embedding Generation Of COVID-19 Spike Sequences
by: Ali, Sarwan, et al.
Published: (2025)

DeepHGNN: Study of Graph Neural Network based Forecasting Methods for Hierarchically Related Multivariate Time Series
by: Sriramulu, Abishek, et al.
Published: (2024)

Context Neural Networks: A Scalable Multivariate Model for Time Series Forecasting
by: Sriramulu, Abishek, et al.
Published: (2024)

Learning to Break Deep Perceptual Hashing: The Use Case NeuralHash
by: Struppek, Lukas, et al.
Published: (2021)

Explaining Categorical Feature Interactions Using Graph Covariance and LLMs
by: Shen, Cencheng, et al.
Published: (2025)

On Probabilistic Embeddings in Optimal Dimension Reduction
by: Murray, Ryan, et al.
Published: (2024)

Reinforcement Learning in Categorical Cybernetics
by: Hedges, Jules, et al.
Published: (2024)

Contextual Bandits with Packing and Covering Constraints: A Modular Lagrangian Approach via Regression
by: Slivkins, Aleksandrs, et al.
Published: (2022)

Generating Poisoning Attacks against Ridge Regression Models with Categorical Features
by: Guedes-Ayala, Monse, et al.
Published: (2025)

A Novel Framework for Online Supervised Learning with Feature Selection
by: Sun, Lizhe, et al.
Published: (2018)

Efficient Online Decision Tree Learning with Active Feature Acquisition
by: Rahbar, Arman, et al.
Published: (2023)

Few-Shot Large Language Models for Actionable Triage Categorization of Online Patient Inquiries
by: Zhou, Liqi, et al.
Published: (2026)

On Understanding Attention-Based In-Context Learning for Categorical Data
by: Wang, Aaron T., et al.
Published: (2024)

Adaptive Regularization for Large-Scale Sparse Feature Embedding Models
by: Li, Mang, et al.
Published: (2025)

Probabilistic Stability Guarantees for Feature Attributions
by: Jin, Helen, et al.
Published: (2025)

Categorical Flow Matching on Statistical Manifolds
by: Cheng, Chaoran, et al.
Published: (2024)

VJEPA: Variational Joint Embedding Predictive Architectures as Probabilistic World Models
by: Huang, Yongchao
Published: (2026)

Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Models
by: An, Ulzee, et al.
Published: (2025)

Hashing for Fast Pattern Set Selection
by: Karjalainen, Maiju, et al.
Published: (2025)