Image de couverture de livre

$σ$-PCA: a building block for neural learning of identifiable linear transformations

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Kanavati, Fahdi, Katsnith, Lucy, Tsuneki, Masayuki
Format:	Preprint
Publié:	2023
Sujets:	Machine Learning Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Predictive representations: building blocks of intelligence
par: Carvalho, Wilka, et autres
Publié: (2024)

Feature learning as alignment: a structural property of gradient descent in non-linear neural networks
par: Beaglehole, Daniel, et autres
Publié: (2024)

Fast weight programming and linear transformers: from machine learning to neurobiology
par: Irie, Kazuki, et autres
Publié: (2025)

Fast and scalable retrosynthetic planning with a transformer neural network and speculative beam search
par: Andronov, Mikhail, et autres
Publié: (2025)

Randomized PCA Forest for Unsupervised Outlier Detection
par: Rajabinasab, Muhammad, et autres
Publié: (2025)

σ-GPTs: A New Approach to Autoregressive Models
par: Pannatier, Arnaud, et autres
Publié: (2024)

Understanding the learned look-ahead behavior of chess neural networks
par: Cruz, Diogo
Publié: (2025)

Adaptive multiple optimal learning factors for neural network training
par: Challagundla, Jeshwanth
Publié: (2024)

A standard transformer and attention with linear biases for molecular conformer generation
par: Gurev, Viatcheslav, et autres
Publié: (2025)

Revisiting PCA for time series reduction in temporal dimension
par: Gao, Jiaxin, et autres
Publié: (2024)

Curvature-Aware PCA with Geodesic Tangent Space Aggregation for Semi-Supervised Learning
par: Levada, Alexandre L. M.
Publié: (2026)

Classification EM-PCA for clustering and embedding
par: Tighidet, Zineddine, et autres
Publié: (2025)

Towards modeling evolving longitudinal health trajectories with a transformer-based deep learning model
par: Moen, Hans, et autres
Publié: (2024)

SUS backprop: linear backpropagation algorithm for long inputs in transformers
par: Pankov, Sergey, et autres
Publié: (2025)

C2G-KD: PCA-Constrained Generator for Data-Free Knowledge Distillation
par: Bengtsson, Magnus, et autres
Publié: (2025)

IntraSlice: Towards High-Performance Structural Pruning with Block-Intra PCA for LLMs
par: Li, Meng, et autres
Publié: (2026)

LLMs learn governing principles of dynamical systems, revealing an in-context neural scaling law
par: Liu, Toni J. B., et autres
Publié: (2024)

Alternative positional encoding functions for neural transformers
par: Lopez-Rubio, Ezequiel, et autres
Publié: (2025)

PREBA: Surgical Duration Prediction via PCA-Weighted Retrieval-Augmented LLMs and Bayesian Averaging Aggregation
par: Wu, Wanyin, et autres
Publié: (2026)

Representations learnt by SGD and Adaptive learning rules: Conditions that vary sparsity and selectivity in neural networks
par: Park, Jin Hyun
Publié: (2022)

Dance recalibration for dance coherency with recurrent convolution block
par: Eum, Seungho, et autres
Publié: (2025)

Target noise: A pre-training based neural network initialization for efficient high resolution learning
par: Wang, Shaowen, et autres
Publié: (2026)

Understanding the theoretical properties of projected Bellman equation, linear Q-learning, and approximate value iteration
par: Lim, Han-Dong, et autres
Publié: (2025)

Application of linear regression and quasi-Newton methods to the deep reinforcement learning in continuous action cases
par: Komatsu, Hisato
Publié: (2025)

A federated learning framework with knowledge graph and temporal transformer for early sepsis prediction in multi-center ICUs
par: Chang, Yue, et autres
Publié: (2026)

Implementation of tangent linear and adjoint models for neural networks based on a compiler library tool
par: Xiao, Sa, et autres
Publié: (2026)

Enhanced QKNorm normalization for neural transformers with the Lp norm
par: Lopez-Rubio, Ezequiel, et autres
Publié: (2026)

A Hybrid PCA-PR-Seq2Seq-Adam-LSTM Framework for Time-Series Power Outage Prediction
par: Das, Subhabrata, et autres
Publié: (2025)

On-site estimation of battery electrochemical parameters via transfer learning based physics-informed neural network approach
par: Yeregui, Josu, et autres
Publié: (2025)

We are not able to identify AI-generated images
par: Pavão, Adrien
Publié: (2025)

Data-driven building energy efficiency prediction using physics-informed neural networks
par: Michalakopoulos, Vasilis, et autres
Publié: (2023)

Efficient and provably convergent end-to-end training of deep neural networks with linear constraints
par: Yang, Zonglin, et autres
Publié: (2026)

Can neural networks do arithmetic? A survey on the elementary numerical skills of state-of-the-art deep learning models
par: Testolin, Alberto
Publié: (2023)

Scalable and reliable deep transfer learning for intelligent fault detection via multi-scale neural processes embedded with knowledge
par: Li, Zhongzhi, et autres
Publié: (2024)

Scaling transformer neural networks for skillful and reliable medium-range weather forecasting
par: Nguyen, Tung, et autres
Publié: (2023)

Inhibitory normalization of error signals improves learning in neural circuits
par: Eyono, Roy Henha, et autres
Publié: (2026)

Context-sensitive neocortical neurons transform the effectiveness and efficiency of neural information processing
par: Ahmed, Khubaib, et autres
Publié: (2022)

PCA-RAG: Principal Component Analysis for Efficient Retrieval-Augmented Generation
par: Khaledian, Arman, et autres
Publié: (2025)

Hidden Convexity of Fair PCA and Fast Solver via Eigenvalue Optimization
par: Shen, Junhui, et autres
Publié: (2025)

A transformer-based deep reinforcement learning approach to spatial navigation in a partially observable Morris Water Maze
par: Eggen, Marte, et autres
Publié: (2024)