Perspectives on Tsallis Statistics for Artificial Intelligence
cs.AI, cs.CE
Submitted: 2026-08-02
Updated: 2026-08-02
Code: https://github.com/Kleyt0n/qjax
Terminology
Sources
- Entropy measures and their applications: A comprehensive review
- Sparse and Continuous Attention Mechanisms
- Sparse Continuous Distributions and Fenchel-Young Losses
- Tsallis Reinforcement Learning: A Unified Framework for Maximum Entropy Reinforcement Learning
- A Theory of Regularized Markov Decision Processes
- Munchausen Reinforcement Learning
- Tsallis-INF: An Optimal Algorithm for Stochastic and Adversarial Bandits
- Why are Adaptive Methods Good for Attention Models?
- Predicting Attention Sparsity in Transformers
- Sparse Graph Attention Networks
- Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning
- Star-Shaped Denoising Diffusion Probabilistic Models
- Two-temperature logistic regression based on the Tsallis divergence
- The q-gradient method for global optimization
- The Heavy-Tail Phenomenon in SGD
- Multiplicative noise and heavy tails in stochastic optimization
- Hausdorff Dimension, Heavy Tails, and Generalization in Neural Networks
- Heavy Tails in SGD and Compressibility of Overparametrized Neural Networks
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