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Interactions among people or objects are often dynamic in nature and can be represented as a sequence of networks, each providing a snapshot of the interactions over a brief period of time. An important task in analyzing such evolving…

Social and Information Networks · Computer Science 2016-06-17 Leto Peel , Aaron Clauset

Finding features that disentangle the different causes of variation in real data is a difficult task, that has nonetheless received considerable attention in static domains like natural images. Interactive environments, in which an agent…

Machine Learning · Computer Science 2017-03-23 Emmanuel Bengio , Valentin Thomas , Joelle Pineau , Doina Precup , Yoshua Bengio

In this paper, we propose a new drag and drop interaction technique for graphs. We designed this interaction to support analysis in complex multidimensional and temporal graphs. The drag and drop interaction is enhanced with an intuitive…

Human-Computer Interaction · Computer Science 2019-02-06 Benjamin Renoust , Haolin Ren , Guy Melançon

In many applications of the probabilistic method, one looks to study phenomena that occur ``with high probability''. More recently however, in an attempt to understand some of the most fundamental problems in combinatorics, researchers have…

Combinatorics · Mathematics 2025-12-18 Julian Sahasrabudhe

In recent years, emotion detection in text has become more popular due to its vast potential applications in marketing, political science, psychology, human-computer interaction, artificial intelligence, etc. Access to a huge amount of…

Computation and Language · Computer Science 2018-06-05 Armin Seyeditabari , Narges Tabari , Wlodek Zadrozny

We present a method of discrete modeling and analysis of multilevel dynamics of complex large-scale hierarchical dynamic systems subject to external dynamic control mechanism. Architectural model of information system supporting simulation…

Computational Engineering, Finance, and Science · Computer Science 2008-09-23 Armen Bagdasaryan

Activation patching is a popular mechanistic interpretability technique, but has many subtleties regarding how it is applied and how one may interpret the results. We provide a summary of advice and best practices, based on our experience…

Machine Learning · Computer Science 2024-04-24 Stefan Heimersheim , Neel Nanda

This paper discusses the mathematical representation of an empirically observed phenomenon, referred to as Incremental Similarity. We discuss this feature from the viewpoint of stochastic processes and present a variety of non-trivial…

Probability · Mathematics 2015-09-23 Ole E. Barndorff-Nielsen , Juergen Schmiegel

Various techniques are used to detect the presence of charged particles stored in electromagnetic traps, their energy, their mass, or their internal states. Detection methods can rely on the variation of the number of trapped particles…

Atomic Physics · Physics 2017-08-23 Martina Knoop

Complex systems have interested researchers across a broad range of fields for many years and as computing has become more accesible and feasible, it is now possible to simulate aspects of these systems. A major point of research is how…

Multiagent Systems · Computer Science 2019-01-16 George Hassan-Coring

We propose a probabilistic formulation that enables sequential detection of multiple change points in a network setting. We present a class of sequential detection rules for certain functionals of change points (minimum among a subset), and…

Statistics Theory · Mathematics 2012-07-09 Arash Ali Amini , XuanLong Nguyen

Interest point detection is a common task in various computer vision applications. Although a big variety of detector are developed so far computational efficiency of interest point based image analysis remains to be the problem. Current…

Computer Vision and Pattern Recognition · Computer Science 2010-03-23 Vitaly Pimenov

In this short note we report on results on a computational search for a counterexample to the strong coincidence conjecture. In particular, we discuss the method used so that further searches can be conducted.

Dynamical Systems · Mathematics 2017-06-19 Scott Balchin

Form a pure mathematical point of view, common functional forms representing different physical phenomena can be defined. For example, rates of chemical reactions, diffusion and heat transfer are all governed by exponential-type…

Machine Learning · Computer Science 2019-10-01 Navid Zobeiry , Keith D. Humfeld

Overview of event-by-event studies on relativistic heavy-ion collisions is given. I focus on fluctuation measurements and on theoretical ideas which appeared experimentally fruitful.

Nuclear Theory · Physics 2009-04-24 Stanislaw Mrowczynski

The novel research area of computational empathy is in its infancy and moving towards developing methods and standards. One major problem is the lack of agreement on the evaluation of empathy in artificial interactive systems. Even though…

Artificial Intelligence · Computer Science 2019-08-16 Özge Nilay Yalçın

Event-Driven Particle Dynamics is a fast and precise method to simulate particulate systems of all scales. In this work it is demonstrated that, despite the high accuracy of the method, the finite machine precision leads to simulations…

Computational Physics · Physics 2014-05-23 Marcus N. Bannerman , Severin Strobl , Arno Formella , Thorsten Poeschel

Emotion can be expressed in many ways that can be seen such as facial expression and gestures, speech and by written text. Emotion Detection in text documents is essentially a content - based classification problem involving concepts from…

Human-Computer Interaction · Computer Science 2012-05-23 Shiv Naresh Shivhare , Saritha Khethawat

The theory of computational complexity focuses on functions and, hence, studies programs whose interactive behavior is reduced to a simple question/answer pattern. We propose a broader theory whose ultimate goal is expressing and analyzing…

Computational Complexity · Computer Science 2012-09-05 Ugo Dal Lago , Tobias Heindel , Damiano Mazza , Daniele Varacca

New technologies have led to vast troves of large and complex datasets across many scientific domains and industries. People routinely use machine learning techniques to not only process, visualize, and make predictions from this big data,…

Machine Learning · Statistics 2023-08-04 Genevera I. Allen , Luqin Gan , Lili Zheng