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We propose BeamTransformer, an efficient architecture to leverage beamformer's edge in spatial filtering and transformer's capability in context sequence modeling. BeamTransformer seeks to optimize modeling of sequential relationship among…

Sound · Computer Science 2021-09-10 Siqi Zheng , Shiliang Zhang , Weilong Huang , Qian Chen , Hongbin Suo , Ming Lei , Jinwei Feng , Zhijie Yan

Reward functions are a common way to specify the objective of a robot. As designing reward functions can be extremely challenging, a more promising approach is to directly learn reward functions from human teachers. Importantly, data from…

The problem of searching for an unknown object occurs in important applications ranging from security, medicine and defense. Sensors with the capability to process information rapidly require adaptive algorithms to control their search in…

Information Theory · Computer Science 2015-08-18 Huanyu Ding , David A. Castañón

The sense of smell is an important part of living organisms. It assists with the interaction of the living organism with its environment. The mechanism by which smell is detected and identified is not fully known. Earlier, shape theory was…

Biological Physics · Physics 2019-11-07 Chukwuemeka Asogwa

Living systems continually respond to signals from the surrounding environment. Survival requires that their responses adapt quickly and robustly to the changes in the environment. One particularly challenging example is olfactory…

Neurons and Cognition · Quantitative Biology 2024-10-08 Kiri Choi , Will Rosenbluth , Isabella R. Graf , Nirag Kadakia , Thierry Emonet

In this paper we study the optimal placement and optimal number of active relay nodes through the traffic density in mobile sensor ad-hoc networks. We consider a setting in which a set of mobile sensor sources is creating data and a set of…

Computer Science and Game Theory · Computer Science 2009-10-30 Alonso Silva , Eitan Altman , Merouane Debbah , Giuseppa Alfano

Statistical matching aims to integrate two statistical sources. These sources can be two samples or a sample and the entire population. If two samples have been selected from the same population and information has been collected on…

Methodology · Statistics 2023-01-04 Raphaël Jauslin , Yves Tillé

Plants monitor their surrounding environment and control their physiological functions by producing an electrical response. We recorded electrical signals from different plants by exposing them to Sodium Chloride (NaCl), Ozone (O3) and…

Radio frequency (RF) signals have facilitated the development of non-contact human monitoring tasks, such as vital signs measurement, activity recognition, and user identification. In some specific scenarios, an RF signal analysis framework…

Search engines answer users' queries by listing relevant items (e.g. documents, songs, products, web pages, ...). These engines rely on algorithms that learn to rank items so as to present an ordered list maximizing the probability that it…

Machine Learning · Computer Science 2021-09-14 Stefan Magureanu , Alexandre Proutiere , Marcus Isaksson , Boxun Zhang

This work considers the problem of detecting signals from multiple sequentially observed data streams, where only one stream can be observed at every time instant. The goal is to detect signals as quickly as possible while controlling the…

Methodology · Statistics 2026-04-07 Yiming Xing , Georgios Fellouris

We present a monolithic, microfabricated, metal-oxide semiconductor (MOS) sensor array in conjunction with a machine learning algorithm to determine unique fingerprints of individual gases within homogenous mixtures. The array comprises…

Applied Physics · Physics 2021-02-26 Noureddine Tayebi , Varvara Kollia , Pradyumna S. Singh

In this paper, we design matched filters for diffusive molecular communication systems taking into account the following impairments: signal-dependent diffusion noise, inter-symbol interference (ISI), and external interfering molecules. The…

Information Theory · Computer Science 2017-05-05 Vahid Jamali , Arman Ahmadzadeh , Robert Schober

We propose a fair machine learning algorithm to model interpretable differences between observed and desired human decision-making, with the latter aimed at reducing disparity in a downstream outcome impacted by the human decision. Prior…

Machine Learning · Computer Science 2025-05-26 Pavan Ravishankar , Rushabh Shah , Daniel B. Neill

We consider the problem of detecting an odd process among a group of Poisson point processes, all having the same rate except the odd process. The actual rates of the odd and non-odd processes are unknown to the decision maker. We consider…

Information Theory · Computer Science 2015-09-24 Nidhin Koshy Vaidhiyan , Rajesh Sundaresan

Learning an ordering of items based on pairwise comparisons is useful when items are difficult to rate consistently on an absolute scale, for example, when annotators have to make subjective assessments. When exhaustive comparison is…

Machine Learning · Computer Science 2024-10-29 Herman Bergström , Emil Carlsson , Devdatt Dubhashi , Fredrik D. Johansson

In this paper, the concept of an adaptation algorithm is proposed, which can be used to blindly adapt the microphone array geometry of a humanoid robot such that the performance of the underlying signal separation algorithm is improved. As…

Sound · Computer Science 2014-04-29 Hendrik Barfuss , Walter Kellermann

Code smells represent sub-optimal implementation choices applied by developers when evolving software systems. The negative impact of code smells has been widely investigated in the past: besides developers' productivity and ability to…

Software Engineering · Computer Science 2019-05-28 Gemma Catolino , Fabio Palomba , Francesca Arcelli Fontana , Andrea De Lucia , Andy Zaidman , Filomena Ferrucci

Given two sources of evidence about a latent variable, one can combine the information from both by multiplying the likelihoods of each piece of evidence. However, when one or both of the observation models are misspecified, the…

Machine Learning · Computer Science 2021-03-24 Dmitrii Krasheninnikov , Rohin Shah , Herke van Hoof

We consider the problem of learning the preferences of a heterogeneous population by observing choices from an assortment of products, ads, or other offerings. Our observation model takes a form common in assortment planning applications:…

Machine Learning · Statistics 2016-06-09 Nathan Kallus , Madeleine Udell