English
Related papers

Related papers: Adversary lower bounds for nonadaptive quantum alg…

200 papers

We develop a novel and generic algorithm for the adversarial multi-armed bandit problem (or more generally the combinatorial semi-bandit problem). When instantiated differently, our algorithm achieves various new data-dependent regret…

Machine Learning · Computer Science 2018-06-08 Chen-Yu Wei , Haipeng Luo

We consider a proximal operator given by a quadratic function subject to bound constraints and give an optimization algorithm using the alternating direction method of multipliers (ADMM). The algorithm is particularly efficient to solve a…

Optimization and Control · Mathematics 2014-12-31 Miguel Á. Carreira-Perpiñán

We study a security threat to adversarial multi-armed bandits, in which an attacker perturbs the loss or reward signal to control the behavior of the victim bandit player. We show that the attacker is able to mislead any no-regret…

Machine Learning · Computer Science 2023-01-31 Yuzhe Ma , Zhijin Zhou

Generally, multi-objective optimisation problems are solved exactly or approximated by solving a series of scalarisations, for example by dichotomic search. In this paper, we take a different approach and attempt to compute the set of all…

Optimization and Control · Mathematics 2026-01-28 Oliver Bachtler , Felix Fritz , Stefan Ruzika

We provide an approach for learning deep neural net representations of models described via conditional moment restrictions. Conditional moment restrictions are widely used, as they are the language by which social scientists describe the…

Econometrics · Economics 2018-04-25 Greg Lewis , Vasilis Syrgkanis

Question answering (QA) systems achieve impressive performance on standard benchmarks like SQuAD, but remain vulnerable to adversarial examples. This project investigates the adversarial robustness of transformer models on the AddSent…

Computation and Language · Computer Science 2026-01-07 Agniv Roy Choudhury , Vignesh Ponselvan Rajasingh

We study the problem of learning predictors that are robust to adversarial examples with respect to an unknown perturbation set, relying instead on interaction with an adversarial attacker or access to attack oracles, examining different…

Machine Learning · Computer Science 2021-02-04 Omar Montasser , Steve Hanneke , Nathan Srebro

We study the fault tolerance of quantum computation by adiabatic evolution, a quantum algorithm for solving various combinatorial search problems. We describe an inherent robustness of adiabatic computation against two kinds of errors,…

Quantum Physics · Physics 2007-05-23 Andrew M. Childs , Edward Farhi , John Preskill

Different techniques have been used to prove several transference theorems of the form "nontrivial algorithms for a circuit class C yield circuit lower bounds against C". In this survey we revisit many of these results. We discuss how…

Computational Complexity · Computer Science 2013-09-03 Igor C. Oliveira

In this work, we study the phase estimation problem. We show an alternative, simpler and self-contained proof of query lower bounds. Technically, compared to the previous proofs [NW99, Bes05], our proof is considerably elementary.…

Quantum Physics · Physics 2023-04-06 Yao-Ting Lin

Neural networks are known to be vulnerable to adversarial examples: inputs that are close to natural inputs but classified incorrectly. In order to better understand the space of adversarial examples, we survey ten recent proposals that are…

Machine Learning · Computer Science 2017-11-02 Nicholas Carlini , David Wagner

Deep neural networks are vulnerable to adversarial examples, which poses security concerns on these algorithms due to the potentially severe consequences. Adversarial attacks serve as an important surrogate to evaluate the robustness of…

Machine Learning · Computer Science 2018-03-23 Yinpeng Dong , Fangzhou Liao , Tianyu Pang , Hang Su , Jun Zhu , Xiaolin Hu , Jianguo Li

We study the complexity of Decoded Quantum Interferometry (DQI), a quantum algorithm for approximate optimization. First, we show that the algorithm resists classical simulation strategies based on locating outputs with large probabilities.…

Quantum Physics · Physics 2026-05-01 Kunal Marwaha , Bill Fefferman , Alexandru Gheorghiu , Vojtech Havlicek

Conditional lower bounds based on $P\neq NP$, the Exponential-Time Hypothesis (ETH), or similar complexity assumptions can provide very useful information about what type of algorithms are likely to be possible. Ideally, such lower bounds…

Computational Complexity · Computer Science 2022-03-16 Dániel Marx

We prove that any exact quantum algorithm searching an ordered list of N elements requires more than \frac{1}{\pi}(\ln(N)-1) queries to the list. This improves upon the previously best known lower bound of {1/12}\log_2(N) - O(1). Our proof…

Quantum Physics · Physics 2007-05-23 Peter Hoyer , Jan Neerbek

We work in the adaptive query model, where one is given a point set $P \subset \mathbb{R}^d$ and seeks to construct a data structure that can answer correctly and efficiently a sequence of adaptive queries. In this model, an adversary…

We prove a query complexity lower bound for $\mathsf{QMA}$ protocols that solve approximate counting: estimating the size of a set given a membership oracle. This gives rise to an oracle $A$ such that $\mathsf{SBP}^A \not\subset…

Computational Complexity · Computer Science 2019-02-08 William Kretschmer

Advances in the effectiveness of machine learning models have come at the cost of enormous complexity resulting in a poor understanding of how they function. Local surrogate methods have been used to approximate the workings of these…

Machine Learning · Computer Science 2025-01-16 Christopher Burger , Charles Walter

We obtain a query lower bound for quantum algorithms solving the phase estimation problem. Our analysis generalizes existing lower bound approaches to the case where the oracle Q is given by controlled powers Q^p of Q, as it is for example…

Quantum Physics · Physics 2007-05-23 Arvid J. Bessen

Adversarial attack algorithms are dominated by penalty methods, which are slow in practice, or more efficient distance-customized methods, which are heavily tailored to the properties of the distance considered. We propose a white-box…

Machine Learning · Computer Science 2021-08-20 Jérôme Rony , Eric Granger , Marco Pedersoli , Ismail Ben Ayed