:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Schiffman, Joshua S.
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2602.22600
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Bellman operator convergence enhancements in reinforcement learning algorithms
by: Kadurha, David Krame, et al.
Published: (2025)

Uncovering mesa-optimization algorithms in Transformers
by: von Oswald, Johannes, et al.
Published: (2023)

Transformers Don't In-Context Learn Least Squares Regression
by: Hill, Joshua, et al.
Published: (2025)

Crystalite: A Lightweight Transformer for Efficient Crystal Modeling
by: Veljković, Tin Hadži, et al.
Published: (2026)

Too Big to Think: Capacity, Memorization, and Generalization in Pre-Trained Transformers
by: Barron, Joshua, et al.
Published: (2025)

Gauge-invariant representation holonomy
by: Sevetlidis, Vasileios, et al.
Published: (2026)

On permutation-invariant neural networks
by: Kimura, Masanari, et al.
Published: (2024)

Learning neuro-symbolic convergent term rewriting systems
by: Petruzzellis, Flavio, et al.
Published: (2025)

Can LLMs predict the convergence of Stochastic Gradient Descent?
by: Zekri, Oussama, et al.
Published: (2024)

Hybrid LSTM-Transformer Models for Profiling Highway-Railway Grade Crossings
by: Chatterjee, Kaustav, et al.
Published: (2025)

Carrying over algorithm in transformers
by: Kruthoff, Jorrit
Published: (2024)

Deep reinforcement learning with time-scale invariant memory
by: Kabir, Md Rysul, et al.
Published: (2024)

Which algorithm to select in sports timetabling?
by: Van Bulck, David, et al.
Published: (2023)

Predicting Stock Movement with BERTweet and Transformers
by: Albada, Michael Charles, et al.
Published: (2025)

The GECo algorithm for Graph Neural Networks Explanation
by: Calderaro, Salvatore, et al.
Published: (2024)

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

The geometry of invariant learning: an information-theoretic analysis of data augmentation and generalization
by: Bouyahia, Abdelali, et al.
Published: (2026)

Causal invariant geographic network representations with feature and structural distribution shifts
by: Wang, Yuhan, et al.
Published: (2025)

Solving the encoding bottleneck: of the HHL algorithm, by the HHL algorithm
by: He, Guang Ping
Published: (2025)

Multiple kernel concept factorization algorithm based on global fusion
by: Li, Fei, et al.
Published: (2024)

Generalizing soft actor-critic algorithms to discrete action spaces
by: Zhang, Le, et al.
Published: (2024)

FRRI: a novel algorithm for fuzzy-rough rule induction
by: Bollaert, Henri, et al.
Published: (2024)

Understanding the performance gap between online and offline alignment algorithms
by: Tang, Yunhao, et al.
Published: (2024)

Conformal Transformations for Symmetric Power Transformers
by: Kumar, Saurabh, et al.
Published: (2025)

IMPaCT GNN: Imposing invariance with Message Passing in Chronological split Temporal Graphs
by: Park, Sejun, et al.
Published: (2024)

Toward TransfORmers: Revolutionizing the Solution of Mixed Integer Programs with Transformers
by: Cooper, Joshua F., et al.
Published: (2024)

Near-optimal algorithms for private estimation and sequential testing of collision probability
by: Busa-Fekete, Robert, et al.
Published: (2025)

An advantage based policy transfer algorithm for reinforcement learning with measures of transferability
by: Alam, Md Ferdous, et al.
Published: (2023)

An information theoretic approach to quantify the stability of feature selection and ranking algorithms
by: Alaiz-Rodriguez, et al.
Published: (2024)

Creating Multi-Level Skill Hierarchies in Reinforcement Learning
by: Evans, Joshua B., et al.
Published: (2023)

Absolute convergence and error thresholds in non-active adaptive sampling
by: Ferro, Manuel Vilares, et al.
Published: (2024)

Domain-invariant Clinical Representation Learning by Bridging Data Distribution Shift across EMR Datasets
by: Zhang, Zhongji, et al.
Published: (2023)

PTSM: Physiology-aware and Task-invariant Spatio-temporal Modeling for Cross-Subject EEG Decoding
by: Jing, Changhong, et al.
Published: (2025)

TOAST: Transformer Optimization using Adaptive and Simple Transformations
by: Cannistraci, Irene, et al.
Published: (2024)

Novel GPU Boruta algorithms for feature selection from high-dimensional data
by: Li, Xurui, et al.
Published: (2026)

Convergence of a model-free entropy-regularized inverse reinforcement learning algorithm
by: Renard, Titouan, et al.
Published: (2024)

Spatial Transformer Network YOLO Model for Agricultural Object Detection
by: Zambre, Yash, et al.
Published: (2024)

An Introduction to Transformers
by: Turner, Richard E.
Published: (2023)

RT-Transformer: The Transformer Block as a Spherical State Estimator
by: Racioppo, Peter
Published: (2026)

Traj-Transformer: Diffusion Models with Transformer for GPS Trajectory Generation
by: Zhang, Zhiyang, et al.
Published: (2025)