:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Simmons, Anj, Barnett, Scott, Chaudhuri, Anupam, Singh, Sankhya, Sivasothy, Shangeetha
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2408.16321
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Quantifying Manifolds: Do the manifolds learned by Generative Adversarial Networks converge to the real data manifold
by: Chaudhuri, Anupam, et al.
Published: (2024)

Detecting out-of-distribution text using topological features of transformer-based language models
by: Pollano, Andres, et al.
Published: (2023)

RAGProbe: An Automated Approach for Evaluating RAG Applications
by: Sivasothy, Shangeetha, et al.
Published: (2024)

Large language models for generating rules, yay or nay?
by: Sivasothy, Shangeetha, et al.
Published: (2024)

Physics-Informed Mixture Models and Surrogate Models for Precision Additive Manufacturing
by: Basterrech, Sebastian, et al.
Published: (2025)

Private Estimation when Data and Privacy Demands are Correlated
by: Chaudhuri, Syomantak, et al.
Published: (2024)

A Theoretical Framework for Grokking: Interpolation followed by Riemannian Norm Minimisation
by: Boursier, Etienne, et al.
Published: (2025)

Understanding and Minimising Outlier Features in Neural Network Training
by: He, Bobby, et al.
Published: (2024)

Minimising Willmore Energy via Neural Flow
by: Hirst, Edward, et al.
Published: (2026)

Testing software for non-discrimination: an updated and extended audit in the Italian car insurance domain
by: Rondina, Marco, et al.
Published: (2025)

Fast hyperboloid decision tree algorithms
by: Chlenski, Philippe, et al.
Published: (2023)

Pragmatic auditing: a pilot-driven approach for auditing Machine Learning systems
by: Benbouzid, Djalel, et al.
Published: (2024)

Mixed-curvature decision trees and random forests
by: Chlenski, Philippe, et al.
Published: (2024)

Asymptotic Characterisation of Robust Empirical Risk Minimisation Performance in the Presence of Outliers
by: Vilucchio, Matteo, et al.
Published: (2023)

Diffusion Alignment Beyond KL: Variance Minimisation as Effective Policy Optimiser
by: Ou, Zijing, et al.
Published: (2026)

Soft decision trees for survival analysis
by: Consolo, Antonio, et al.
Published: (2025)

Reinforcement Learning for Synchronised Flow Control in a Dual-Gate Resin Infusion System
by: Camacho-Sánchez, Miguel, et al.
Published: (2025)

Proper decision trees: An axiomatic framework for solving optimal decision tree problems with arbitrary splitting rules
by: He, Xi, et al.
Published: (2025)

An Empirical Study of Scaling Laws for Transfer
by: Barnett, Matthew
Published: (2024)

Splitting criteria for ordinal decision trees: an experimental study
by: Ayllón-Gavilán, Rafael, et al.
Published: (2024)

Analyzing decision tree bias towards the minority class
by: Phelps, Nathan, et al.
Published: (2025)

Optimal hypersurface decision trees
by: He, Xi
Published: (2025)

Minimisation of Polyak-Łojasewicz Functions Using Random Zeroth-Order Oracles
by: Farzin, Amir Ali, et al.
Published: (2024)

QUCE: The Minimisation and Quantification of Path-Based Uncertainty for Generative Counterfactual Explanations
by: Duell, Jamie, et al.
Published: (2024)

Interpretable clustering via optimal multiway-split decision trees
by: Suzuki, Hayato, et al.
Published: (2026)

A moving target in AI-assisted decision-making: Dataset shift, model updating, and the problem of update opacity
by: Hatherley, Joshua
Published: (2025)

Compute Requirements for Algorithmic Innovation in Frontier AI Models
by: Barnett, Peter
Published: (2025)

Driving Assistance System for Ambulances to Minimise the Vibrations in Patient Cabin
by: Aldegheishem, Abdulaziz, et al.
Published: (2026)

ODTE -- An ensemble of multi-class SVM-based oblique decision trees
by: Montañana, Ricardo, et al.
Published: (2024)

Minimisation of Submodular Functions Using Gaussian Zeroth-Order Random Oracles
by: Farzin, Amir Ali, et al.
Published: (2025)

Under manipulations, are some AI models harder to audit?
by: Godinot, Augustin, et al.
Published: (2024)

CCAR: Intrinsic Robustness as an Emergent Geometric Property
by: Samanta, Akash, et al.
Published: (2026)

Approximating splits for decision trees quickly in sparse data streams
by: Tatti, Nikolaj
Published: (2026)

Better Trees: An empirical study on hyperparameter tuning of classification decision tree induction algorithms
by: Mantovani, Rafael Gomes, et al.
Published: (2018)

Minimisation of Quasar-Convex Functions Using Random Zeroth-Order Oracles
by: Farzin, Amir Ali, et al.
Published: (2025)

Distribution Learning with Valid Outputs Beyond the Worst-Case
by: Rittler, Nick, et al.
Published: (2024)

A Closer Look at the Learnability of Out-of-Distribution (OOD) Detection
by: Garov, Konstantin, et al.
Published: (2025)

A novel gradient-based method for decision trees optimizing arbitrary differential loss functions
by: Konstantinov, Andrei V., et al.
Published: (2025)

Des-q: a quantum algorithm to provably speedup retraining of decision trees
by: Kumar, Niraj, et al.
Published: (2023)

Robust Unsupervised Adaptation of a Speech Recogniser Using Entropy Minimisation and Speaker Codes
by: van Dalen, Rogier C., et al.
Published: (2025)