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Two special situations where the standard uncertainty product inequality appears to be useless are modified. One such case is noted to also trivialize the recently-introduced alternatives [Phys. Rev. Lett. 113, 260401 (2014); Sci. Rep. 6,…

Quantum Physics · Physics 2016-12-30 Kamal Bhattacharyya

A machine learning model is calibrated if its predicted probability for an outcome matches the observed frequency for that outcome conditional on the model prediction. This property has become increasingly important as the impact of machine…

Machine Learning · Computer Science 2025-02-25 Muthu Chidambaram , Rong Ge

Providing explanations about how machine learning algorithms work and/or make particular predictions is one of the main tools that can be used to improve their trusworthiness, fairness and robustness. Among the most intuitive type of…

Machine Learning · Computer Science 2024-04-12 Rubén Ruiz-Torrubiano

We again consider (as in a companion paper) an entangled two-particle state that is produced from two independent down-conversion sources by the process of "entanglement-swapping", so that the particles have never met. We show that there is…

Quantum Physics · Physics 2008-08-01 Daniel Greenberger , Michael Horne , Anton Zeilinger , Marek Zukowski

Across machine learning (ML) sub-disciplines, researchers make explicit mathematical assumptions in order to facilitate proof-writing. We note that, specifically in the area of fairness-accuracy trade-off optimization scholarship, similar…

Computers and Society · Computer Science 2021-09-09 A. Feder Cooper , Ellen Abrams

To steer language models towards truthful outputs on tasks which are beyond human capability, previous work has suggested training models on easy tasks to steer them on harder ones (easy-to-hard generalization), or using unsupervised…

Machine Learning · Computer Science 2026-02-25 Callum Canavan , Aditya Shrivastava , Allison Qi , Jonathan Michala , Fabien Roger

Quantum computing hardware has grown sufficiently complex that it often can no longer be simulated by classical computers, but its computational power remains limited by errors. These errors corrupt the results of quantum algorithms, and it…

Despite recent progress on conversational systems, they still do not perform smoothly and coherently when faced with ambiguous requests. When questions are unclear, conversational systems should have the ability to ask clarifying questions,…

Information Retrieval · Computer Science 2022-08-10 Negar Arabzadeh , Mahsa Seifikar , Charles L. A. Clarke

Suppose we want to implement a unitary $U$, for instance a circuit for some quantum algorithm. Suppose our actual implementation is a unitary $\tilde{U}$, which we can only apply as a black-box. In general it is an exponentially-hard task…

Quantum Physics · Physics 2021-04-21 Noah Linden , Ronald de Wolf

Bipartite and multipartite entangled states are basic ingredients for constructing quantum networks and their accurate verification is crucial to the functioning of the networks, especially for untrusted networks. Here we propose a simple…

Quantum Physics · Physics 2021-12-28 Yun-Guang Han , Zihao Li , Yukun Wang , Huangjun Zhu

Many robotics applications require alignment and fusion of observations obtained at multiple views to form a global model of the environment. Multi-way data association methods provide a mechanism to improve alignment accuracy of pairwise…

Robotics · Computer Science 2020-03-06 Kaveh Fathian , Kasra Khosoussi , Yulun Tian , Parker Lusk , Jonathan P. How

Systems of polynomial equations over an algebraically-closed field K can be used to concisely model many combinatorial problems. In this way, a combinatorial problem is feasible (e.g., a graph is 3-colorable, hamiltonian, etc.) if and only…

Combinatorics · Mathematics 2008-01-25 J. A. De Loera , J. Lee , P. Malkin , S. Margulies

Discussions of statistical criteria for fairness commonly convey the normative significance of calibration within groups by invoking what risk scores "mean." On the Same Meaning picture, group-calibrated scores "mean the same thing" (on…

Machine Learning · Computer Science 2025-03-18 Lily Hu

We conjecture a new entropic uncertainty principle governing the entropy of complementary observations made on a system given side information in the form of quantum states, generalizing the entropic uncertainty relation of Maassen and…

Quantum Physics · Physics 2009-07-10 Joseph M. Renes , Jean-Christian Boileau

We analyze a mixed quantum-classical algorithm recently derived from the exact factorization equations [Min, Agostini, Gross, PRL {\bf 115}, 073001 (2015)] to show the role of the different terms in the algorithm in bringing about…

Chemical Physics · Physics 2018-05-10 Graeme H. Gossel , Federica Agostini , Neepa T. Maitra

We propose a novel algorithm for learning fair representations that can simultaneously mitigate two notions of disparity among different demographic subgroups in the classification setting. Two key components underpinning the design of our…

Machine Learning · Computer Science 2020-02-18 Han Zhao , Amanda Coston , Tameem Adel , Geoffrey J. Gordon

Conformal prediction is often calibrated with a single pooled threshold, but this can hide cross-group heterogeneity in score distributions and distort group-wise coverage. We study this phenomenon through the population score distributions…

Machine Learning · Statistics 2026-05-18 Ziang Gao , Pengqi Liu , Archer Yi Yang , Mouloud Belbahri , Jesse C. Cresswell , Masoud Asgharian

We consider N quantum systems initially prepared in pure states and address the problem of unambiguously comparing them. One may ask whether or not all $N$ systems are in the same state. Alternatively, one may ask whether or not the states…

Quantum Physics · Physics 2014-11-18 Anthony Chefles , Erika Andersson , Igor Jex

This paper corrects the proof of the Theorem 2 from the Gower's paper \cite[page 5]{Gower:1982} as well as corrects the Theorem 7 from Gower's paper \cite{Gower:1986}. The first correction is needed in order to establish the existence of…

Machine Learning · Computer Science 2018-12-24 Mieczysław A. Kłopotek

The coalgebraic $\mu$-calculus provides a generic semantic framework for fixpoint logics over systems whose branching type goes beyond the standard relational setup, e.g. probabilistic, weighted, or game-based. Previous work on the…

Logic in Computer Science · Computer Science 2024-08-07 Daniel Hausmann , Lutz Schröder