Copertina

Measuring IIA Violations in Similarity Choices with Bayesian Models

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Corrêa, Hugo Sales, Sankagiri, Suryanarayana, Figueiredo, Daniel Ratton, Grossglauser, Matthias
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning I.2.6
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Fusing Rewards and Preferences in Reinforcement Learning
di: Khorasani, Sadegh, et al.
Pubblicazione: (2025)

Hierarchical Reinforcement Learning with Targeted Causal Interventions
di: Khorasani, Sadegh, et al.
Pubblicazione: (2025)

Efficiently Escaping Saddle Points for Policy Optimization
di: Khorasani, Sadegh, et al.
Pubblicazione: (2023)

The Bayesian Confidence (BACON) Estimator for Deep Neural Networks
di: Kee, Patrick D., et al.
Pubblicazione: (2024)

ACE: Exploring Activation Cosine Similarity and Variance for Accurate and Calibration-Efficient LLM Pruning
di: Mi, Zhendong, et al.
Pubblicazione: (2025)

Multiple Token Divergence: Measuring and Steering In-Context Computation Density
di: Herrmann, Vincent, et al.
Pubblicazione: (2025)

Measuring In-Context Computation Complexity via Hidden State Prediction
di: Herrmann, Vincent, et al.
Pubblicazione: (2025)

Entropy-Based Measurement of Value Drift and Alignment Work in Large Language Models
di: Fadli, Samih
Pubblicazione: (2025)

Deep Memory Search: A Metaheuristic Approach for Optimizing Heuristic Search
di: Hedar, Abdel-Rahman, et al.
Pubblicazione: (2024)

Inference Time Causal Probing in LLMs
di: Khorasani, Sadegh, et al.
Pubblicazione: (2026)

Almost Equivariance via Lie Algebra Convolutions
di: McNeela, Daniel
Pubblicazione: (2023)

Bayesian Hierarchical Probabilistic Forecasting of Intraday Electricity Prices
di: Nickelsen, Daniel, et al.
Pubblicazione: (2024)

FluidWorld: Reaction-Diffusion Dynamics as a Predictive Substrate for World Models
di: Polly, Fabien
Pubblicazione: (2026)

Scaling Laws for Neural Material Models
di: Trikha, Akshay, et al.
Pubblicazione: (2025)

Downsized and Compromised?: Assessing the Faithfulness of Model Compression
di: Kamal, Moumita, et al.
Pubblicazione: (2025)

Seasoning Generative Models for a Generalization Aftertaste
di: Husain, Hisham, et al.
Pubblicazione: (2026)

Explanations Based on Item Response Theory (eXirt): A Model-Specific Method to Explain Tree-Ensemble Model in Trust Perspective
di: Ribeiro, José, et al.
Pubblicazione: (2022)

AI and Machine Learning Approaches for Predicting Nanoparticles Toxicity The Critical Role of Physiochemical Properties
di: Yousaf, Iqra
Pubblicazione: (2024)

Tempered Calculus for ML: Application to Hyperbolic Model Embedding
di: Nock, Richard, et al.
Pubblicazione: (2024)

CASSANDRA: Programmatic and Probabilistic Learning and Inference for Stochastic World Modeling
di: Lymperopoulos, Panagiotis, et al.
Pubblicazione: (2026)

TFMAdapter: Lightweight Instance-Level Adaptation of Foundation Models for Forecasting with Covariates
di: Dange, Afrin, et al.
Pubblicazione: (2025)

Securing Reliability: A Brief Overview on Enhancing In-Context Learning for Foundation Models
di: Huang, Yunpeng, et al.
Pubblicazione: (2024)

Identifying Policy Gradient Subspaces
di: Schneider, Jan, et al.
Pubblicazione: (2024)

HGCN(O): A Self-Tuning GCN HyperModel Toolkit for Outcome Prediction in Event-Sequence Data
di: Wang, Fang, et al.
Pubblicazione: (2025)

CoxSE: Exploring the Potential of Self-Explaining Neural Networks with Cox Proportional Hazards Model for Survival Analysis
di: Alabdallah, Abdallah, et al.
Pubblicazione: (2024)

Adaptive Candidate Point Thompson Sampling for High-Dimensional Bayesian Optimization
di: Fan, Donney, et al.
Pubblicazione: (2026)

A Simple Approximate Bayesian Inference Neural Surrogate for Stochastic Petri Net Models
di: Manu, Bright Kwaku, et al.
Pubblicazione: (2025)

2Mamba2Furious: Linear in Complexity, Competitive in Accuracy
di: Mongaras, Gabriel, et al.
Pubblicazione: (2026)

Mean-Pooled Cosine Similarity is Not Length-Invariant: Theory and Cross-Domain Evidence for a Length-Invariant Alternative
di: Mitra, Sibayan, et al.
Pubblicazione: (2026)

Learning To Help: Training Models to Assist Legacy Devices
di: Wu, Yu, et al.
Pubblicazione: (2024)

Learned Relay Representations for Forward-Thinking Discrete Diffusion Models
di: Rozonoyer, Benjamin, et al.
Pubblicazione: (2026)

Variance Is Not Importance: Structural Analysis of Transformer Compressibility Across Model Scales
di: Salfati, Samuel
Pubblicazione: (2026)

Evaluating the Systematic Reasoning Abilities of Large Language Models through Graph Coloring
di: Heyman, Alex, et al.
Pubblicazione: (2025)

Quantifying the Energy Floor: Direct Measurement and Replay Buffer Bias in SAC-Based HVAC Control on sbsim
di: Li, Bo, et al.
Pubblicazione: (2026)

Kolmogorov Arnold Networks and Multi-Layer Perceptrons: A Paradigm Shift in Neural Modelling
di: Gaonkar, Aradhya, et al.
Pubblicazione: (2026)

Transformer Scalability Crisis: The First Comprehensive Empirical Analysis of Performance Walls in Modern Language Models
di: Moghadasi, Mahdi Naser, et al.
Pubblicazione: (2026)

I-GLIDE: Input Groups for Latent Health Indicators in Degradation Estimation
di: Thil, Lucas, et al.
Pubblicazione: (2025)

RobustModelMaker: Coupling Bootstrap Stability Selection with Leakage-Safe Nested Cross-Validation for Scientific Machine Learning
di: Barnard, Amanda S
Pubblicazione: (2026)

SmallML: Bayesian Transfer Learning for Small-Data Predictive Analytics
di: Leontev, Semen
Pubblicazione: (2025)

FSC-Net: Fast-Slow Consolidation Networks for Continual Learning
di: Gorrim, Mohamed El
Pubblicazione: (2025)