Conferences  >  Informatics  >  Algorithms and Data Structures

Neural Networks and Artificial Intelligence, Machine Learning,    Implementation and Applications of Artificial Intelligence

SBA Research

ARES is ranked as B-conference in CORE.

Conference Management;     Email: ares@sba-research.org

Authorization, Authentication, and Access Control Automated Vulnerability Repair Availability, Confidentiality, Integrity Botnets and Botnet Monitoring Cloud Security Compliance, Certification and Legal aspects related to Security and Privacy Dependability, and Resilience Digital Forensics Human Factors in Security and Privacy Identity Management Incident Response and Prevention Intrusion Detection and Fraud Detection Machine Learning for Security and Privacy Security and Privacy for Machine Learning Mobile Security Network Security Privacy-Enhancing Technologies (PETs) Process based Security Models and Methods Risk analysis Side Channel Attacks Software Security Static and Dynamic Code Analysis for Security and Privacy Security and Privacy for IoT, Cyber-Physical Systems, and Critical Infrastructures Security and Privacy Awareness Security Requirements and Secure Design of Applications Usable Security and Privacy Threats and Attack Modelling Trusted Computing Trust Models and Trust Management Web Application Security and Privacy

Information Security and Information Privacy,    Digital Forensics

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

Schloss Dagstuhl - Leibniz-Zentrum für Informatik

Fair division concerns the allocation of resources to a set of interested entities, according to some fairness criteria. Fair division has remained an active research area over the years, attracting the attention of several scientific disciplines, such as mathematics, computer science, game theory, and political science. Especially within the last two decades, this area has gradually drawn significantly more attention, due to the emergence of novel solution concepts, algorithmic techniques, and promising applications. It has also gained increasing popularity within computer science, since many of the field's key questions are inherently algorithmic. Consequently, there has been a notable growth of the relevant literature by now, spanning numerous fascinating research directions.

USENIX Association

SREcon24 Europe/Middle East/Africa is a gathering of engineers who care deeply about site reliability, systems engineering, and working with complex distributed systems at scale. SREcon strives to challenge both those new to the profession as well as those who have been involved in it for decades. The conference has a culture of critical thought, deep technical insights, continuous improvement, and innovation.

Software Engineering,    High Performance Computing, Supercomputing, Parallel Computing

Institute for Computational and Experimental Research in Mathematics (ICERM)

In this workshop, we will consider challenges and best practices in translating theory to software for phylogenetic inference. We will discuss strategies adopted by the tool development community, their relative advantages, and lessons learned through software development. We will discuss a variety of objective functions (parametric and non-parametric) and algorithmic techniques used by inference methods. We will cover parallelization and how it interacts with the choice of objective function and algorithmic technique. Finally, we will discuss best practices for evaluating new and existing software tools, not just to validate the implementation but also to study accuracy and scalability in relation to theory and usage in realistic bioinformatics pipelines. In addition to discussing how theory influences tools, we will examine how tool development can inform the theoretical questions asked.

ICERM;     Email: info@icerm.brown.edu

bioinformatics, phylogenetic inference, software development

Society for Industrial and Applied Mathematics (SIAM)

Society for Industrial and Applied Mathematics (SIAM)

Society for Industrial and Applied Mathematics (SIAM)

The International Conference on Algorithms and Discrete Applied Mathematics (CALDAM), held under the aegis of the Association of Computer Science and Discrete Mathematics (ACSDM), is intended to bring together researchers working in the areas of Algorithms and Applied Discrete Mathematics and provide a high-quality forum for the dissemination and discussion of research results in these broad areas.

Applied Mathematics (in general),    Numerical Analysis and Computational Mathematics

Algorithms and Logic Group @ University of Electronic Science and Technology of China , Theoretical Computer Science Committee of China Computer Federation (CCF)

Applied Mathematics (in general),    Numerical Analysis and Computational Mathematics

USENIX Association

SREcon is a gathering of engineers who care deeply about site reliability, systems engineering, and working with complex distributed systems at scale. Our purpose is to be inclusive as we bring together ideas representative of our diverse community, whether its members are focusing on a global scale, launching new products and ideas for a small business, or pivoting their approach to unite software and systems engineering. SREcon challenges both those new to the profession as well as those who have been involved in it for decades. The conference has a culture of critical thought, deep technical insights, continuous improvement, and innovation.

Software Engineering,    High Performance Computing, Supercomputing, Parallel Computing

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

A long-standing question in theoretical computer science is to offer analysis tools for improving performance on typical everyday, non-worst-case instances. A recent model addressing this goal is the algorithms-with-predictions model: each problem instance comes with a possibly error-prone prediction, and the worst-case running time is given as a function of the error in that prediction. This model reflects how recent advances in machine learning are able to make reasonably good predictions on practical ‒ even very complex ‒ datasets. The algorithms-with-predictions model has been used to give strong approximation-ratio guarantees for fundamental online algorithms like scheduling and caching. How to leverage predictions to speed up running time of offline algorithms and data structures has received less attention. This Dagstuhl Seminar aims to bring together researchers from the data structures, combinatorial optimization and learned predictions communities to address the challenges of adopting learned predictions for improving running time guarantees.

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

Computational geometry is concerned with the design, analysis, and implementation of algorithms for geometric and topological problems, which arise naturally in a wide range of areas, including computer graphics, CAD, robotics, computer vision, image processing, spatial databases, GIS, molecular biology, sensor networks, machine learning, data mining, scientific computing, theoretical computer science, and pure mathematics. Computational geometry is a vibrant and mature field of research, with several dedicated international conferences and journals and strong intellectual connections with other computing and mathematics disciplines. The emphasis of the Dagstuhl Seminar is on presenting recent developments in computational geometry, as well as identifying new challenges, opportunities, and connections to other fields of computing.

The general topic of the conference is the theory and application of discrete ​structures. Its goal is to highlight the most salient trends in the field, which has ​close links to diverse areas such as cryptography, computer science, large-scale ​networks and biology. Particular areas of interest include: graphs and digraphs, ​hypergraphs, matroids, ordered sets, designs, coding theory, enumeration, ​combinatorics of words, discrete optimization, discrete and computational ​geometry, lattice point enumeration, combinatorial algorithms, computational ​complexity, and applications of discrete and algorithmic mathematics, including ​(but not limited to) web graphs, computational biology, telecommunication ​networks, and information processing.

Applied Mathematics (in general),    Numerical Analysis and Computational Mathematics

Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH

Constraint optimization is today a de facto practical approach to efficiently solving various types of NP-hard optimization problems arising from real-world settings. This is primarily due to significant advances in practical algorithms and implementation-level techniques, which have resulted in increasingly efficient and robust constraint optimization solvers for a range of NP-hard declarative languages. However, the need for even more efficient and robust constraint optimization solvers continues to grow, as in several contexts more and more complex optimization problems need to be solved.