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ABC algorithms are notoriously expensive in computing time, as they require simulating many complete artificial datasets from the model. We advocate in this paper a "divide and conquer" approach to ABC, where we split the likelihood into n…

Computation · Statistics 2015-12-02 Simon Barthelmé , Nicolas Chopin , Vincent Cottet

We present randomized approximation algorithms for multi-criteria Max-TSP. For Max-STSP with k > 1 objective functions, we obtain an approximation ratio of $1/k - \eps$ for arbitrarily small $\eps > 0$. For Max-ATSP with k objective…

Data Structures and Algorithms · Computer Science 2008-12-18 Markus Bläser , Bodo Manthey , Oliver Putz

We establish tight bounds on the amount on nonuniformity that is necessary for extracting a string with randomness rate 1 from a single source of randomness with lower randomness rate. More precisely, as instantiations of more general…

Computational Complexity · Computer Science 2012-05-01 Marius Zimand

We introduce a simple model illustrating the role of context in communication and the challenge posed by uncertainty of knowledge of context. We consider a variant of distributional communication complexity where Alice gets some information…

Computational Complexity · Computer Science 2015-07-21 Badih Ghazi , Ilan Komargodski , Pravesh Kothari , Madhu Sudan

Each vertex of an arbitrary simple graph on $n$ vertices chooses $k$ random incident edges. What is the expected number of edges in the original graph that connect different connected components of the sampled subgraph? We prove that the…

Discrete Mathematics · Computer Science 2019-09-26 Jacob Holm , Valerie King , Mikkel Thorup , Or Zamir , Uri Zwick

We consider the sorted top-$k$ problem whose goal is to recover the top-$k$ items with the correct order out of $n$ items using pairwise comparisons. In many applications, multiple rounds of interaction can be costly. We restrict our…

Data Structures and Algorithms · Computer Science 2019-06-13 Mark Braverman , Jieming Mao , Yuval Peres

In this paper, new inner and outer bounds on the achievable compression-equivocation rate region for generalized secure data compression with side information are given that do not match in general. In this setup, two senders, Alice and…

Information Theory · Computer Science 2010-04-07 Somayeh Salimi , Mahmoud Salmasizadeh , Mohammad Reza Aref

We propose a bipartite quantum key distribution (QKD) protocol based on causal nonseparability: the presence of a resource -- a process matrix -- that does not correspond to any definite causal order between two parties. In our protocol,…

We investigate the possibility of eavesdropping on a quantum key distribution network by local sequential quantum unsharp measurement attacks by the eavesdropper. In particular, we consider a pure two-qubit state shared between two parties…

Quantum Physics · Physics 2023-12-08 Yash Wath , Hariprasad M , Freya Shah , Shashank Gupta

Let us consider $k ~(\ge 2)$ independent populations $\Pi_1, \ldots,\Pi_k$, where $\Pi_i$ follows exponential distribution with hazard rate ${\sigma_i},$ ($i = 1,\ldots,k$). Suppose $Y_{i1},\ldots, Y_{in}$ be a random sample of size $n$…

Statistics Theory · Mathematics 2021-07-09 Brijesh Kumar Jha , Ajaya Kumar Mahapatra , Suchandan Kayal

We provide a simple method to obtain an upper bound on the secret key rate that is particularly suited to analyze practical realizations of quantum key distribution protocols with imperfect devices. We consider the so-called trusted device…

Quantum Physics · Physics 2009-11-11 Tobias Moroder , Marcos Curty , Norbert Lütkenhaus

A random k-out mapping (digraph) on [n] is generated by choosing k random images of each vertex one at a time, subject to a "preferential attachment" rule: the current vertex selects an image i with probability proportional to a given…

Combinatorics · Mathematics 2014-08-25 Nicholas R. Peterson , Boris Pittel

Top-$k$ decoding is a widely used method for sampling from LLMs: at each token, only the largest $k$ next-token-probabilities are kept, and the next token is sampled after re-normalizing them to sum to unity. Top-$k$ and other sampling…

Artificial Intelligence · Computer Science 2026-02-24 Georgy Noarov , Soham Mallick , Tao Wang , Sunay Joshi , Yan Sun , Yangxinyu Xie , Mengxin Yu , Edgar Dobriban

We consider the average-consensus problem in a multi-node network of finite size. Communication between nodes is modeled by a sequence of directed signals with arbitrary communication delays. Four distributed algorithms that achieve…

Distributed, Parallel, and Cluster Computing · Computer Science 2011-06-23 Kevin Topley , Vikram Krishnamurthy

A dealer aims to share a secret with participants so that only predefined subsets can reconstruct it, while others learn nothing. The dealer and participants access correlated randomness and communicate over a one-way, public, rate-limited…

Information Theory · Computer Science 2026-01-27 Rumia Sultana , Remi A. Chou

We consider the problem of uniform sampling of points on an algebraic variety. Specifically, we develop a randomized algorithm that, given a small set of multivariate polynomials over a sufficiently large finite field, produces a common…

Data Structures and Algorithms · Computer Science 2009-02-10 Mahdi Cheraghchi , Amin Shokrollahi

Separation of competing speech is a key challenge in signal processing and a feat routinely performed by the human auditory brain. A long standing benchmark of the spectrogram approach to source separation is known as the ideal binary mask.…

Sound · Computer Science 2015-03-25 Andrew J. R. Simpson

We consider the asymmetric simple exclusion process (ASEP) on the integers in which the initial density at a site (the probability that it is occupied) is given by a periodic function on the positive integers. (When the function is constant…

Probability · Mathematics 2011-02-23 Craig A. Tracy , Harold Widom

We consider the communication scenario where K transmitters are each connected to a common receiver with an orthogonal noiseless link. One of the transmitters has a message for the receiver, who is prohibited from learning anything in the…

Information Theory · Computer Science 2018-04-05 Hua Sun

1-bit compressive sensing aims to recover sparse signals from quantized 1-bit measurements. Designing efficient approaches that could handle noisy 1-bit measurements is important in a variety of applications. In this paper we use the…

Information Theory · Computer Science 2022-04-28 Shuai Huang , Trac D. Tran