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In a recent article entitled "A simple explanation of the quantum violation of a fundamental inequality," Cabello proposes a condition on a class of probabilistic models that, he claims, gives the same bound on contextuality for the KCBS…

Quantum Physics · Physics 2012-10-25 Joe Henson

Scientific discovery increasingly requires learning on federated datasets, fed by streams from high-resolution instruments, that have extreme class imbalance. Current ML approaches either require impractical data aggregation or fail due to…

Machine Learning · Computer Science 2026-03-16 Md Anwar Hossen , Nathan R. Tallent , Luanzheng Guo , Ali Jannesary

Quantum cognition often explains order effects, contextuality, and violations of the law of total probability by replacing classical probability with quantum probability on a fixed event structure. This paper proposes a different…

Artificial Intelligence · Computer Science 2026-05-26 Song-Ju Kim

I assess various proposals for the source of the intuition that there is something problematic about contextuality, ultimately concluding that contextuality is best thought of in terms of fine-tuning. I then argue that as with other…

Quantum Physics · Physics 2021-11-24 Emily Adlam

We introduce a taxonomy for partially coherent optical fields spanning multiple degrees of freedom (DoFs) based on the rank of the associated coherence matrix (the number of non-zero eigenvalues). When DoFs comprise two spatial modes and…

In many instances in first order logic or computable algebra, classical theorems show that many problems are undecidable for general structures, but become decidable if some rigidity is imposed on the structure. For example, the set of…

Discrete Mathematics · Computer Science 2017-08-08 Emmanuel Jeandel

Identifying when observed statistics cannot be explained by any reasonable classical model is a central problem in quantum foundations. A principled and universally applicable approach to defining and identifying nonclassicality is given by…

In a noncontextual hidden variable model of quantum theory, hidden variables determine the outcomes of every measurement in a manner that is independent of how the measurement is implemented. Using a generalization of this notion to…

Quantum Physics · Physics 2009-01-09 Robert W. Spekkens , D. H. Buzacott , A. J. Keehn , Ben Toner , G. J. Pryde

A notion of morphism that is suitable for the sheaf-theoretic approach to contextuality is developed, resulting in a resource theory for contextuality. The key features involve using an underlying relation rather than a function between…

Quantum Physics · Physics 2019-01-30 Martti Karvonen

Knowledge graph completion (KGC) aims to automatically infer missing facts in multi-relational data by mapping entities and relations into continuous representation spaces. Recent region-based embedding models have shown great promise in…

Machine Learning · Computer Science 2026-05-13 Yingqi Zeng , Luying Wang , Huiling Zhu

When it isn't possible to tell two distinct experimental procedures apart purely from their input/output statistics, then it seems a plausible hypothesis that the two procedures must be physically identical. We call such a hypothesis…

Quantum Physics · Physics 2021-02-17 Ravi Kunjwal

Most scholars maintain that quantum mechanics (QM) is a contextual theory and that quantum probability does not allow an epistemic (ignorance) interpretation. By inquiring possible connections between contextuality and non-classical…

Quantum Physics · Physics 2021-12-13 Claudio Garola

Matrix and tensor-guided parametrization for Natural Language Processing (NLP) models is fundamentally useful for the improvement of the model's systematic efficiency. However, the internal links between these two algebra structures and…

Computation and Language · Computer Science 2024-10-07 Mingxue Xu , Sadia Sharmin , Danilo P. Mandic

The prevailing approach to improving large language model (LLM) reasoning has centered on expanding context windows, implicitly assuming that more tokens yield better performance. However, empirical evidence - including the "lost in the…

Artificial Intelligence · Computer Science 2026-03-24 Zihua Wu , Georg Gartner

Our starting point is a particular `canvas' aimed to `draw' theories of physics, which has symmetric monoidal categories as its mathematical backbone. In this paper we consider the conceptual foundations for this canvas, and how these can…

Quantum Physics · Physics 2010-09-21 Bob Coecke

This work focuses on off-policy evaluation (OPE) with function approximation in infinite-horizon undiscounted Markov decision processes (MDPs). For MDPs that are ergodic and linear (i.e. where rewards and dynamics are linear in some known…

Machine Learning · Computer Science 2020-06-24 Nevena Lazic , Dong Yin , Mehrdad Farajtabar , Nir Levine , Dilan Gorur , Chris Harris , Dale Schuurmans

Observable properties of a classical physical system can be modelled deterministically as functions from the space of pure states to outcomes; dually, states can be modelled as functions from the algebra of observables to outcomes. The…

Operator Algebras · Mathematics 2021-03-09 Nadish de Silva , Rui Soares Barbosa

This paper proposes an algebraic framework for analyzing event execution intervals and sequences, introducing "Optional Intervals Event (OIE)" as a 4-tuple abstraction (C, F, I, A) that serves as a pre-execution planning tool for real-world…

General Mathematics · Mathematics 2026-05-20 Zhongyuan. Li , Yanlei. Gong , Lei. Yu , Yue. Cao , Bo. Yin

Off-policy evaluation (OPE) is the problem of estimating the value of a target policy using historical data collected under a different logging policy. OPE methods typically assume overlap between the target and logging policy, enabling…

Methodology · Statistics 2024-03-12 Samir Khan , Martin Saveski , Johan Ugander

Despite the growing interest in replicating the scaled success of large language models (LLMs) in industrial search and recommender systems, most existing industrial efforts remain limited to transplanting Transformer architectures, which…