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International Conference on Algorithmic Learning Theory

Proceedings of Machine Learning Research

International Conference on Algorithmic Learning Theory (ALT)

Name: Algorithmic Learning Theory
Start: 2023-02-20
End: 2023-02-23
Location: Singapore

Location: Singapore , Singapore

Submission deadline: 9/30/2022

Conference dates: 2/20/2023 - 2/23/2023

Research H-index

Official website

Ranking & Metrics

Discipline name	Position	Best Scientists	Publications	D-Index
Computer Science	357	31	29	10

Call for Papers

The Algorithmic Learning Theory (ALT) 2023 conference will be held in Singapore on Feb 20-23, 2023. The conference is dedicated to all theoretical and algorithmic aspects of machine learning. We invite submissions with contributions to new or existing learning problems including, but not limited to:

Design and analysis of learning algorithms.
Statistical and computational learning theory.
Online learning algorithms and theory.
Optimization methods for learning.
Unsupervised, semi-supervised, and active learning.
Interactive learning, planning and control, and reinforcement learning.
Privacy-preserving data analysis.
Learning with additional societal and strategic considerations: e.g., fairness, economics.
Robustness of learning algorithms to adversarial agents.
Artificial neural networks, including deep learning.
High-dimensional and non-parametric statistics.
Adaptive data analysis and selective inference.
Learning with algebraic or combinatorial structure.
Bayesian methods in learning.
Learning in distributed and streaming settings.
Game theory and learning.
Learning from complex data: e.g., networks, time series.
Theoretical analysis of probabilistic graphical models.

Overview

This ranking presents a comprehensive evaluation of scientific conferences within the field of Computer Science. The ranking has been meticulously prepared by Research.com, a leading website renowned for its trusted data on scientific contributions and rigorous coverage of all major research fields, including Computer Science, since 2014.

Conference positions within the ranking are determined by a unique bibliometric score devised by Research.com. This score is calculated based on a combination of the estimated h-index and the number of leading scientists who have participated in each conference over the past three years. Such a multifaceted approach ensures that the resulting rankings effectively reflect both the scholarly impact of the conferences and their significance within the expert community.

The ranking incorporates Impact Score values collected as of 2024-11-27, representing the most up-to-date and relevant data available. The analysis process was extensive, involving the assessment of over 2,742 conferences. These were selected following a detailed inspection and rigorous examination of more than 148,739 scientific documents published during the most recent three-year period by 13,184 highly respected scientists in Computer Science.

This robust methodology underscores the depth of expert research and the complexity of analysis that underpins the resulting rankings, ensuring their reliability and value to the academic community. For a detailed explanation of the methodology used to compute the ranking scores, please refer to our Methodology Page.

Papers citation over time

A key indicator for each conference is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

Top authors and change over time

The top authors publishing at Algorithmic Learning Theory (based on the number of publications) are:

Marcus Hutter (14 papers) absent at the last edition,
Sandra Zilles (12 papers) published 1 paper at the last edition the same number as at the previous edition,
Sanjay Jain (9 papers) published 1 paper at the last edition, 1 less than at the previous edition,
Tor Lattimore (9 papers) published 1 paper at the last edition,
Frank Stephan (9 papers) absent at the last edition.

The overall trend for top authors publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top authors.

Top affiliations and change over time

Only papers with recognized affiliations are considered

The top affiliations publishing at Algorithmic Learning Theory (based on the number of publications) are:

Google (16 papers) published 7 papers at the last edition, 2 more than at the previous edition,
Technion – Israel Institute of Technology (16 papers) published 3 papers at the last edition the same number as at the previous edition,
Australian National University (13 papers) absent at the last edition,
National University of Singapore (13 papers) published 1 paper at the last edition, 1 less than at the previous edition,
University of Regina (12 papers) published 1 paper at the last edition the same number as at the previous edition.

The overall trend for top affiliations publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions at the conference edition to all articles published within that conference. The best research institutions were selected based on the largest number of articles published during all editions of the conference.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2019 edition, 50.00% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 24.29% were posted by at least one author from the top 10 institutions publishing at the conference. Another 14.29% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 18.57% of all publications and 42.86% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of conferences they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same conference from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the conference in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing at a conference. The index includes the authors publishing at the last edition of a conference, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

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