7 papers · 1 filter
A Note on How to Remove the Term from the Squint Bound
Francesco Orabona
In Orabona and Pál [2016], we introduced the shifted KT potentials, to remove the factor in the parameter-free learning with expert bound. In this short technical note,…
A Best-of-Both-Worlds Proof for Tsallis-INF without Fenchel Conjugates
Wei-Cheng Lee, Francesco Orabona
In this short note, we present a simple derivation of the best-of-both-world guarantee for the Tsallis-INF multi-armed bandit algorithm from J. Zimmert and Y. Seldin. Tsallis-INF:…
Beyond the Ideal: Analyzing the Inexact Muon Update
Egor Shulgin, Sultan AlRashed, Francesco Orabona +1
The Muon optimizer has rapidly emerged as a powerful, geometry-aware alternative to AdamW, demonstrating strong performance in large-scale training of neural networks. However, a c…
Position: Machine Learning Conferences Should Establish a "Refutations and Critiques" Track
Rylan Schaeffer, Joshua Kazdan, Yegor Denisov-Blanch +11
Science progresses by iteratively advancing and correcting humanity's understanding of the world. In machine learning (ML) research, rapid advancements have led to an explosion of…
A Robust Rate for Unprojected TD Learning with Linear Function Approximation
Wei-Cheng Lee, Francesco Orabona
We investigate the finite-time convergence properties of Temporal Difference (TD) learning with linear function approximation, a cornerstone of reinforcement learning. We are inter…
STaR-Bets: Sequential Target-Recalculating Bets for Tighter Confidence Intervals
Václav Voráček, Francesco Orabona
The construction of confidence intervals for the mean of a bounded random variable is a classical problem in statistics with numerous applications in machine learning and virtually…
ATA: Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning
Artavazd Maranjyan, El Mehdi Saad, Peter Richtárik +1
Asynchronous methods are fundamental for parallelizing computations in distributed machine learning. They aim to accelerate training by fully utilizing all available resources. How…