Copertina

Flows on convex polytopes

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Diederen, Tomek, Zamboni, Nicola
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Emergent Compositional Communication for Latent World Properties
di: Kaszyński, Tomek
Pubblicazione: (2026)

Convergence of gradient flow for learning convolutional neural networks
di: Diederen, Jona-Maria, et al.
Pubblicazione: (2026)

Scalable Multi-Agent Offline Reinforcement Learning and the Role of Information
di: Zamboni, Riccardo, et al.
Pubblicazione: (2025)

Training Agents to Self-Report Misbehavior
di: Lee, Bruce W., et al.
Pubblicazione: (2026)

Towards Principled Unsupervised Multi-Agent Reinforcement Learning
di: Zamboni, Riccardo, et al.
Pubblicazione: (2025)

The Limits of Pure Exploration in POMDPs: When the Observation Entropy is Enough
di: Zamboni, Riccardo, et al.
Pubblicazione: (2024)

Enhancing Diversity in Parallel Agents: A Maximum State Entropy Exploration Story
di: De Paola, Vincenzo, et al.
Pubblicazione: (2025)

K-Myriad: Jump-starting reinforcement learning with unsupervised parallel agents
di: De Paola, Vincenzo, et al.
Pubblicazione: (2026)

ParallelFlow: Parallelizing Linear Transformers via Flow Discretization
di: Cirone, Nicola Muca, et al.
Pubblicazione: (2025)

Few measurement shots challenge generalization in learning to classify entanglement
di: Banchi, Leonardo, et al.
Pubblicazione: (2024)

Evaluating Angle and Amplitude Encoding Strategies for Variational Quantum Machine Learning: their impact on model's accuracy
di: Tudisco, Antonio, et al.
Pubblicazione: (2025)

From Parameters to Behaviors: Unsupervised Compression of the Policy Space
di: Tenedini, Davide, et al.
Pubblicazione: (2025)

How to Explore with Belief: State Entropy Maximization in POMDPs
di: Zamboni, Riccardo, et al.
Pubblicazione: (2024)

Run-Time Monitoring of ERTMS/ETCS Control Flow by Process Mining
di: Vitale, Francesco, et al.
Pubblicazione: (2025)

Unsupervised Behavioral Compression: Learning Low-Dimensional Policy Manifolds through State-Occupancy Matching
di: Fraschini, Andrea, et al.
Pubblicazione: (2026)

Multi-Marginal Flow Matching with Adversarially Learnt Interpolants
di: Kviman, Oskar, et al.
Pubblicazione: (2025)

The Nyström method for convex loss functions
di: Della Vecchia, Andrea, et al.
Pubblicazione: (2020)

Probing Dec-POMDP Reasoning in Cooperative MARL
di: Tessera, Kale-ab, et al.
Pubblicazione: (2026)

MicroFlow: An Efficient Rust-Based Inference Engine for TinyML
di: Carnelos, Matteo, et al.
Pubblicazione: (2024)

Online Non-convex Optimization with Long-term Non-convex Constraints
di: Pan, Shijie, et al.
Pubblicazione: (2023)

Async Control: Stress-testing Asynchronous Control Measures for LLM Agents
di: Stickland, Asa Cooper, et al.
Pubblicazione: (2025)

Enforcing convex constraints in Graph Neural Networks
di: Rashwan, Ahmed, et al.
Pubblicazione: (2025)

Fundamental Limitations in Pointwise Defences of LLM Finetuning APIs
di: Davies, Xander, et al.
Pubblicazione: (2025)

FlowMAC: Conditional Flow Matching for Audio Coding at Low Bit Rates
di: Pia, Nicola, et al.
Pubblicazione: (2024)

Remembering the Markov Property in Cooperative MARL
di: Tessera, Kale-ab Abebe, et al.
Pubblicazione: (2025)

Denoising data using convex relaxations
di: Fefferman, Charles, et al.
Pubblicazione: (2026)

Near-optimal delta-convex estimation of Lipschitz functions
di: Balázs, Gábor
Pubblicazione: (2025)

A lift for input-convex neural network training
di: Siahkoohi, Ali, et al.
Pubblicazione: (2026)

Differentially Private Non-convex Distributionally Robust Optimization
di: Xu, Difei, et al.
Pubblicazione: (2026)

Optimal Stochastic Non-smooth Non-convex Optimization through Online-to-Non-convex Conversion
di: Cutkosky, Ashok, et al.
Pubblicazione: (2023)

Tightening convex relaxations of trained neural networks: a unified approach for convex and S-shaped activations
di: Carrasco, Pablo, et al.
Pubblicazione: (2024)

Strong convexity-guided hyper-parameter optimization for flatter losses
di: Yedida, Rahul, et al.
Pubblicazione: (2024)

Distributional simplicity bias and effective convexity in Energy Based Models
di: Decelle, Aurélien, et al.
Pubblicazione: (2026)

On amortizing convex conjugates for optimal transport
di: Amos, Brandon
Pubblicazione: (2022)

Smoothing ADMM for Non-convex and Non-smooth Hierarchical Federated Learning
di: Mirzaeifard, Reza, et al.
Pubblicazione: (2025)

Large-Scale Non-convex Stochastic Constrained Distributionally Robust Optimization
di: Zhang, Qi, et al.
Pubblicazione: (2024)

Exploring the loss landscape of regularized neural networks via convex duality
di: Kim, Sungyoon, et al.
Pubblicazione: (2024)

High-probability zeroth-order online convex optimisation beyond Euclidean geometry
di: Janz, David, et al.
Pubblicazione: (2025)

A Saddle Point Remedy: Power of Variable Elimination in Non-convex Optimization
di: Gan, Min, et al.
Pubblicazione: (2025)

Single-loop Algorithms for Stochastic Non-convex Optimization with Weakly-Convex Constraints
di: Yang, Ming, et al.
Pubblicazione: (2025)