Ranking & Metrics
Impact Score is a novel metric devised to rank conferences based on the number of contributing the best scientists in addition to the h-index estimated from the scientific papers published by the best scientists. See more details on our methodology page.

Research Impact Score:32.40

Contributing Best Scientists:805

H5-index:

Papers published by Best Scientists1644

Research Ranking (Computer Science)5

Conference Call for Papers

Topics of interest include (but are not limited to):

General Machine Learning (active learning, clustering, online learning, ranking, reinforcement learning, semi-supervised learning, time series analysis, unsupervised learning, etc.)

Deep Learning (architectures, generative models, deep reinforcement learning, etc.)

Learning Theory (bandits, game theory, statistical learning theory, etc.)

Optimization (convex and non-convex optimization, matrix/tensor methods, sparsity, etc.)

Probabilistic Inference (Bayesian methods, graphical models, Monte Carlo methods, etc.)

We encourage the submission of papers that develop machine learning techniques to address socially relevant problems, ethical AI and AI safety.

Overview

Top Research Topics at International Conference on Machine Learning?

Artificial intelligence (42.54%)

Machine learning (22.37%)

Algorithm (15.66%)

The topics of Artificial intelligence, Machine learning, Algorithm, Mathematical optimization and Pattern recognition are the focal point of discussions in the conference.
The conference dives deep in exploring the relationship between the study of Artificial intelligence and Task (project management).
Most of the Machine learning studies addressed also intersect with Data mining.

What are the most cited papers published at the conference?

Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data (11653 citations)

Rectified Linear Units Improve Restricted Boltzmann Machines (8679 citations)

Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (7587 citations)

Research areas of the most cited articles at International Conference on Machine Learning:

The published articles mostly deal with topics like Artificial intelligence, Machine learning, Pattern recognition, Mathematical optimization and Algorithm.
Artificial intelligence study tackled in the published articles is connected to the field of Data mining.
Many of the studies tackled in the conference papers connect Machine learning with a similar field of study like Multi-task learning.

What topics the last edition of the conference is best known for?

Artificial intelligence

Statistics

Machine learning

The previous edition focused in particular on these issues:

The conference mostly deals with topics like Artificial intelligence, Algorithm, Machine learning, Reinforcement learning and Mathematical optimization.
In addition to Artificial intelligence research, it aims to explore topics under Generalization, Task (project management) and Pattern recognition.
The conference explores topics in Machine learning which can be helpful for research in disciplines like Robustness (computer science) and Code (cryptography).

The studies tackled, which mainly focus on Mathematical optimization, apply to Convergence (routing) as well.

The most cited articles from the last conference are:

Training data-efficient image transformers & distillation through attention (63 citations)

SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning (27 citations)

WILDS: A Benchmark of in-the-Wild Distribution Shifts (22 citations)

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.

Research.com

Top authors and change over time

The top authors publishing at International Conference on Machine Learning (based on the number of publications) are:

Michael I. Jordan (65 papers) published 3 papers at the last edition, 6 less than at the previous edition,

Masashi Sugiyama (53 papers) published 14 papers at the last edition, 2 more than at the previous edition,

Zoubin Ghahramani (51 papers) absent at the last edition,

Lawrence Carin (51 papers) absent at the last edition,

Shie Mannor (48 papers) published 5 papers at the last edition, 3 more than at the previous 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.

Research.com

Top affiliations and change over time

Only papers with recognized affiliations are considered

The top affiliations publishing at International Conference on Machine Learning (based on the number of publications) are:

Google (582 papers) published 129 papers at the last edition, 3 more than at the previous edition,

Carnegie Mellon University (485 papers) published 62 papers at the last edition, 11 more than at the previous edition,

Stanford University (389 papers) published 70 papers at the last edition, 2 more than at the previous edition,

Microsoft (383 papers) published 62 papers at the last edition, 6 more than at the previous edition,

University of California, Berkeley (362 papers) published 66 papers at the last edition, 8 less than 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.

Research.com

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.

Research.com

During the most recent 2021 edition, 3.47% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 34.58% were posted by at least one author from the top 10 institutions publishing at the conference. Another 14.14% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 20.15% of all publications and 31.14% 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.

Research.com

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.

Research.com

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).

Research.com

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