Maximization

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Period ending 2026-09-14

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Breaking the $T^{3/4}$ Barrier for Regret Minimization With Bi-Dimensional CDFs
Jul 22, 2026Matteo Castiglioni, Anna Lunghi, Alberto MarchesiO(T^Β)$ Simultaneous Regret Regret
Making Single-Cell Data Distillation Auditable: Traceable Real-Cell Coresets via Discrete Min--Max Selection
Jul 20, 2026Yaodi Luo, Peize He, Lingbei Meng +4Single-Cell Rna Sequencing Geometry-Aware Uncertainty Coresets
Autoresearch with Coding Agents: Generalizers and Metric-Maximizers on Quran Recitation Data
Jul 20, 2026Nursultan Askarbekuly, Mohamad Al Mdfaa, Ahmed Helaly +2Coding Agents Autoresearch
Lighthouse RL: Sample-Efficient Circuit Optimization via Strategic Reset Points
Jul 15, 2026Mustafa Emre Gürsoy, Stefan Uhlich, Ryoga Matsuo +6Analog Circuits Deep Reinforcement Learning
Forgetful Attention: A Trainable Support-Vector Memory with Certified Selection and Exact Unlearning
Jul 13, 2026Vishwajith RameshSoftmax Attention Forgetting
Optimizing ARDL Models for Retail Sales Forecasting and Fair Pricing
Jul 10, 2026Sujay Uday RittikarDemand Forecasting Prices
Sensitivity to Subjective Expected Utility Maximization: A Methodological Study, with an Illustrative Application to LLM Decision-Making
Jul 8, 2026Jeff HelznerExpected Utility Decisions
Autonomous UAV Route Planning for Coverage Maximization in Environmental Monitoring: A Systematic Literature Review
Jul 3, 2026Sebastian Jouannet-Contreras, Carola Figueroa-FloresUnmanned Aerial Vehicle Trajectories Coverage Path Planning
Open Problem: Is Interaction Necessary for Order-Optimal 1-bit Mean Estimation?
Jul 3, 2026Ivan Lau, Jonathan ScarlettMaximization Nonparametric
Improved Runtime Bound for the $(μ+ 1)$ EA on BinVal
Jun 11, 2026Joris Belder, Johannes Lengler, Raghu Raman RaviBinary Upper Bounds
Runtime Analysis of a Compact Genetic Algorithm on a Truly Multi-valued OneMax Function
May 28, 2026Martin S. Krejca, Carsten WittGenetic Algorithms Maximization
Implicit Bias of Mirror Flow in Homogeneous Neural Networks: Sparse and Dense Feature Learning
May 19, 2026Tom Jacobs, Guido MontufarFeature Learning Gradient Flow
Neural Acceleration for Graph Partitioning
May 18, 2026Joshua Dennis Booth, Vishvam PatelPartitioning Graph Laplacians
Profit Maximization in Bilateral Trade against a Smooth Adversary
May 12, 2026Simone Di Gregorio, Paul Dütting, Federico Fusco +1Maximization Adversaries
Constraint-Data-Value-Maximization: Utilizing Data Attribution for Effective Data Pruning in Low-Data Environments
May 11, 2026Danilo Brajovic, David A. Kreplin, Marco F. HuberHeterogeneous Pruning Scores Pruning
FPGA-Based Hardware Architecture for Contrast Maximization in Event-Based Vision
May 10, 2026Michal Filipkowski, Marcin Kowalczyk, Tomasz KryjakField-Programmable Gate Arrays Vision Sensors
ZScribbleSeg: A comprehensive segmentation framework with modeling of efficient annotation and maximization of scribble supervision
May 7, 2026Ke Zhang, Bomin Wang, Hangqi Zhou +1Medical Image Segmentation Scratch
Unifying Goal-Conditioned RL and Unsupervised Skill Learning via Control-Maximization
May 7, 2026Alireza Modirshanechi, Benjamin Eysenbach, Peter Dayan +1Goal-Conditioned Reinforcement Learning Unsupervised Skill Discovery
Joint Energy Management and Coordinated AIGC Workload Scheduling for Distributed Data Centers: A Diffusion-Aided Reward Shaping Approach
May 3, 2026Yang Fu, Peng Qin, Liming Chen +3Artificial Intelligence Data Centers Data Centers
On the Learning Curves of Revenue Maximization
Apr 29, 2026Steve Hanneke, Alkis Kalavasis, Shay Moran +1Optimal Sample Complexity Maximization
Sparse Graph Learning from Sparse Data via Fiedler Number Maximization
Apr 28, 2026Bahar Oveisgharan, Gene Cheung, Andrew EckfordGraph Laplacians Sparsity
Stochastic simultaneous optimistic optimization
Apr 27, 2026Michal Valko, Alexandra Carpentier, Rémi MunosStochastic Optimization Maximization
An Elementary Proof of the Near Optimality of LogSumExp Smoothing
Dec 11, 2025Thabo Samakhoana, Benjamin GrimmerMaximization Smoothing
Gaussian process policy iteration with additive Schwarz acceleration for forward and inverse HJB and mean field game problems
May 1, 2025Xianjin Yang, Jingguo ZhangHamilton-Jacobi Reachability Gaussian Process

Jul 22, 2026 · cs.LGJ/K move · Enter open · S save

Breaking the $T^{3/4}$ Barrier for Regret Minimization With Bi-Dimensional CDFs

Matteo Castiglioni, Anna Lunghi, Alberto Marchesi

Politecnico di Milano

We study regret minimization for learning CDF-related objectives of the form

g(x)\cdot\mathbb{P}_{X\sim\mathcal{D}}(X\le x),

over

[0,1]^2

, where

g

is a known Lipschitz function and

\mathcal{D}

is an unknown distribution. At each round

t

, the learner selects a point

x_t

and observes the binary feedback

\mathbb{I}(X_t\le x_t)

, where

X_t\sim\mathcal{D}

. We design an algorithm achieving regret

\widetilde{\mathcal{O}}(T^{7/10})

, improving over the previous best-known bound of

\widetilde{\mathcal{O}}(T^{3/4})

and showing that the curse of dimensionality can be at least partially lifted for this class of objectives, though a gap remains with the

Ω(T^{2/3})

lower bound. As an application, our techniques yield the same

\widetilde{\mathcal{O}}(T^{7/10})

regret bound for profit maximization in repeated bilateral trade with fixed prices.

O(T^Β)$ Simultaneous Regret Regret Maximization Lipschitz Constant Feedback Learning

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