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17,191 papers

#machine learning Preprint Oct 2026

Measurement-Efficient Differentiable Quantum Architecture Search for Combinatorial Optimization

This work shows that for a broad class of combinatorial optimization problems and commonly used rotational gate parameterizations, the measurement cost of DQAS can be significantly reduced without changing the optimization objective.

Lukas Theißinger, Thore Gerlach, Christian Bauckhage · 0 citations
#machine learning Preprint Oct 2026

Dataset Pruning from First Principles: A Label-Free Linear Programming Approach

Dataset pruning reduces a large training set to a representative subset while preserving model performance. Existing geometry-based methods typically assume that nearby points in embedding space share similar properties. Rather than imposing this assumption, we derive geometric selection criteria by reformulating unbia...

Rodrigo Schuller, Francisco Ganacim · 0 citations
#machine learning Preprint Oct 2026

Data Reuse in Non-Stationary Learning

This paper proposes a class of anytime algorithms, dubbed Exposure-Capped Reuse (ECR), that combine online change detection, compatibility testing, and contamination control, and derives a novel information-theoretic lower bound that establishes the near-minimax optimality of ECR.

Tomer Gafni, Garud Iyengar, A. Zeevi · 0 citations
#machine learning Preprint Open access Oct 2026

Estimating Uncoded Crash Factors with Tabular Foundation and System One Models: Kumo Tabular and Jev

Road safety programs count the coded fields of police crash records, while the officer's narrative, which often records factors the fields omit, is rarely read. A safety office thus cannot tell how much its counts miss or where to review. This study develops and evaluates a system that joins both views of the 5,601,890...

Amir Rafe, Subasish Das · 0 citations
#machine learning Preprint Open access Oct 2026

Energy-Efficient Gait Adaptation via Hierarchical Reinforcement Learning for Quadrupedal Locomotion Across Diverse Terrains

While energy efficiency is a critical objective for legged-robot locomotion control, achieving low energy consumption while maintaining robust performance across different velocity ranges and terrain conditions remains a key challenge. This is particularly true for end-to-end RL policies, where gait generation, motion...

Ammar Issa, Anubhav Singh, Anton Tsaritsin et al. · 0 citations
#machine learning Preprint Oct 2026

Temporal Visuo-Tactile Learning for Dexterous Grasp Stability

Results show how rich fingertip sensing and expressive temporal models that capture the dynamics of touch can support learned grasping with multi-fingered hands without explicit contact or force modeling, providing a scalable data-driven path from tactile experience toward stable dexterous manipulation.

Ken Nakahara, Aleksei Buvailik, P. Kotov et al. · 0 citations
#machine learning Preprint Oct 2026

Neural Sampling with Reweighted Normalizing Flows via the Wasserstein--Fisher--Rao JKO Scheme

We propose a neural algorithm for sampling from distributions specified by unnormalized Boltzmann densities. Our approach is based on the Jordan--Kinderlehrer--Otto scheme for the Kullback--Leibler divergence in the Wasserstein--Fisher--Rao geometry (WFR JKO scheme). Our contributions are twofold. First, we prove that,...

Chen-Guang Duan, J. Hertrich, G. Steidl · 0 citations
#machine learning Preprint Open access Oct 2026

Using Small Language Models to Reverse-Engineer Machine Learning Pipelines Structures

Context: Once defined a taxonomy of stages structuring Machine Learning (ML) pipelines (e.g. Data Preprocessing, Modeling...), extracting these stages from source code is key for better understanding ML practices. However, the diversity caused by the constant evolution of ML (e.g., algorithms, datasets) makes this task...

Nicolas Lacroix, Frederic Precioso, Mireille Blay-Fornarino et al. · 0 citations
#machine learning Preprint Oct 2026

On the Cyclic Assumption of the Cow-Path Search Algorithm

In the cow-path problem, a cow must find a goal lying at an unknown distance on one of $w$ paths connected only at the origin, and performance is measured by competitive ratio. Kao, Reif and Tate designed an efficient randomized algorithm in which the cow visits the paths in a fixed cyclic order. They proved the algori...

Yuan Ma, Y. Yin · 0 citations
#machine learning Preprint Open access Oct 2026

RoBART: Bayesian Additive Regression Trees with Tree-Specific Rotations

Bayesian additive regression trees (BART) can require many splits to approximate boundaries misaligned with the predictor axes. RoBART assigns each tree a rotation shared by all internal nodes, retaining axis-aligned splits in rotated coordinates and constant leaves. We jointly propose a Givens rotation sequence and cu...

Jeongung Heo, Seonghyun Jeong · 0 citations
#machine learning Preprint Open access Oct 2026

CARES: A Controlled Synthetic Benchmark of Speaker Reactions to Sound

Automatic audio scene description turns a recording into a text account of a situation. One difficulty is deciding which elements of the audio should be kept, since a description cannot include them all. Annotators disagree about this, making a ground truth hard to obtain. In this work, we first define the ground truth...

Marcel Gibier, Thomas Thebaud, Olivier Bo\"effard et al. · 0 citations
#machine learning Preprint Open access Oct 2026

Computations of the slice genus and the unknotting number of links via machine learning

Links are disjoint unions of circles smoothly embedded in $S^3$. We use reinforcement learning and Bayesian optimisation to obtain new upper bounds on several link invariants that are not known to be algorithmically computable: the slice genus and the unknotting number for links, and the strong slice genus for algebrai...

Yutong Dai, Oliver Hayman, Andr\'as Juh\'asz et al. · 0 citations

From tech blogs

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Microsoft Research Blog Nov 3, 2026

Learn the rules: The hacker mindset

Research Manager Mike Walker reflects on a career spanning hacker culture, cybersecurity, and AI, sharing lessons about trust, teamwork, leadership, and why solving difficult problems requires curiosity, judgment, agility—and an understanding of the rules. The post Learn the rules: The hacker mindset appeared first on Microsoft Research.

Google DeepMind Blog Nov 3, 2026

Agentic cheminformatics with Google Antigravity

Learn how Google Antigravity and our Cheminformatics Skills accelerate drug discovery workflows, search compounds, and propose novel rigidified macrocycles.

MIT News · Artificial Intelligence Oct 28, 2026

Making machines that can listen

Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.

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