Martin Takáč

5.4k citations
59 papers · 1.7k indexed · 1 hit paper · h-index 17
Topics
Stochastic Gradient Optimization Techniques (23 papers)Sparse and Compressive Sensing Techniques (21 papers)Child and Animal Learning Development (7 papers)
Journals
SHILAP Revista de lepidopterologíaActa MaterialiaThe Journal of Physical Chemistry C

In The Last Decade

Martin Takáč

51 papers receiving 1.6k citations

Hit Papers

Iteration complexity of randomized block-coordinate desce...20122026201620212012100200300

Peers

Martin Takáč
Comparison fields: 5 of 119
  • Artificial Intelligence 895
  • Computational Mechanics 528
  • Civil and Structural Engineering 241
  • Computer Networks and Communications 233
  • Electrical and Electronic Engineering 160
Replace Yi Zhou with:
Yi Zhou China
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Vincent Wertz Belgium
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Citations per field
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Citations per year

Countries citing papers authored by Martin Takáč

Since Specialization
Citations

This map shows the geographic impact of Martin Takáč's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Martin Takáč with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Martin Takáč more than expected).

Fields of papers citing papers by Martin Takáč

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Martin Takáč. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Martin Takáč. The network helps show where Martin Takáč may publish in the future.

Co-authorship network of co-authors of Martin Takáč

This figure shows the co-authorship network connecting the top 25 collaborators of Martin Takáč. A scholar is included among the top collaborators of Martin Takáč based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Martin Takáč. Martin Takáč is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 2
3 1
4 1
5 0
6 0
7 7
8 2
9 6
10 5
11 4
12
SGD and Hogwild! Convergence Without the Bounded Gradients Assumption
14
13
Distributed Hessian-Free Optimization for Deep Neural Network.
2
14
A Deep Q-Network for the Beer Game with Partial Information.
6
15
Working memory encoding of events and their participants: a neural network model with applications in sensorimotor processing and sentence generation.
3
16
Mechanisms for storing and accessing event representations in episodic memory, and their expression in language: a neural network model.
3
17 7
18
A neural network model of working memory for episodes
1
19
Mini-Batch Primal and Dual Methods for SVMs
31
20 19

About Martin Takáč

Martin Takáč is a scholar working on Computational Mathematics, Computational Mechanics and Artificial Intelligence, having authored 59 papers that have together received 1.7k indexed citations. Recurring topics across this work include Stochastic Gradient Optimization Techniques (23 papers), Sparse and Compressive Sensing Techniques (21 papers) and Child and Animal Learning Development (7 papers). The work is most often cited by research in Numerical Analysis (156 citations), Artificial Intelligence (895 citations) and Computational Mechanics (528 citations). Martin Takáč has collaborated with scholars based in United States, United Arab Emirates and Slovakia. Frequent co-authors include Peter Richtárik, Shamim N. Pakzad, Jakub Konečný, Martin Jaggi, Michael I. Jordan, Virginia Smith, Jie Liu, Soheil Sadeghi Eshkevari, Mohammadreza Nazari and Lawrence Snyder. Their work appears in journals such as SHILAP Revista de lepidopterología, Acta Materialia and The Journal of Physical Chemistry C.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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