Andrej Risteski

1.1k total citations
17 papers, 218 citations indexed

About

Andrej Risteski is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Andrej Risteski has authored 17 papers receiving a total of 218 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 2 papers in Computer Networks and Communications. Recurrent topics in Andrej Risteski's work include Topic Modeling (5 papers), Natural Language Processing Techniques (4 papers) and Machine Learning and Data Classification (3 papers). Andrej Risteski is often cited by papers focused on Topic Modeling (5 papers), Natural Language Processing Techniques (4 papers) and Machine Learning and Data Classification (3 papers). Andrej Risteski collaborates with scholars based in United States, Austria and Poland. Andrej Risteski's co-authors include Sanjeev Arora, Yuanzhi Li, Tengyu Ma, Yingyu Liang, Yi Zhang, Mikhail Khodak, Christiane Fellbaum, Elan Rosenfeld, Pradeep Ravikumar and Rong Ge and has published in prestigious journals such as Transactions of the Association for Computational Linguistics, arXiv (Cornell University) and Neural Information Processing Systems.

In The Last Decade

Andrej Risteski

17 papers receiving 209 citations

Peers

Countries citing papers authored by Andrej Risteski

Since Specialization

Citations

This map shows the geographic impact of Andrej Risteski'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 Andrej Risteski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrej Risteski more than expected).

Fields of papers citing papers by Andrej Risteski

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andrej Risteski. 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 Andrej Risteski. The network helps show where Andrej Risteski may publish in the future.

Co-authorship network of co-authors of Andrej Risteski

This figure shows the co-authorship network connecting the top 25 collaborators of Andrej Risteski. A scholar is included among the top collaborators of Andrej Risteski 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 Andrej Risteski. Andrej Risteski is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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17 of 17 papers shown

#	Work	Indexed citations
1	Universal Approximation Using Well-Conditioned Normalizing Flows 2021 ·Neural Information Processing Systems ·(unknown), (unknown), (unknown), Andrej Risteski	3
2	The Risks of Invariant Risk Minimization 2021 ·arXiv (Cornell University) ·Elan Rosenfeld, Pradeep Ravikumar, Andrej Risteski	5
3	On Learning Language-Invariant Representations for Universal Machine Translation 2020 ·arXiv (Cornell University) ·Han Zhao, Junjie Hu, Andrej Risteski	2
4	Benefits of Overparameterization in Single-Layer Latent Variable Generative Models. 2019 ·arXiv (Cornell University) ·(unknown), Andrej Risteski, Yoni Halpern, David Sontag	1
5	Empirical Study of the Benefits of Overparameterization in Learning Latent Variable Models 2019 ·arXiv (Cornell University) ·(unknown), Yoni Halpern, Yoon Kim, Andrej Risteski, David Sontag	3
6	Do GANs learn the distribution? Some Theory and Empirics 2018 ·International Conference on Learning Representations ·Sanjeev Arora, Andrej Risteski, Yi Zhang	44
7	Beyond Log-concavity: Provable Guarantees for Sampling Multi-modal Distributions using Simulated Tempering Langevin Monte Carlo 2018 ·arXiv (Cornell University) ·(unknown), Andrej Risteski, Rong Ge	5
8	The Comparative Power of ReLU Networks and Polynomial Kernels in the Presence of Sparse Latent Structure 2018 ·International Conference on Learning Representations ·(unknown), Andrej Risteski	1
9	On the ability of neural nets to express distributions 2017 ·Conference on Learning Theory ·(unknown), Rong Ge, Tengyu Ma, Andrej Risteski, Sanjeev Arora	4
10	Automated WordNet Construction Using Word Embeddings 2017 ·Mikhail Khodak, Andrej Risteski, Christiane Fellbaum, Sanjeev Arora	15
11	Provable learning of noisy-OR networks 2017 ·Sanjeev Arora, Rong Ge, Tengyu Ma, Andrej Risteski	6
12	Algorithms and matching lower bounds for approximately-convex optimization 2016 ·Neural Information Processing Systems ·Yuanzhi Li, Andrej Risteski	5
13	On Routing Disjoint Paths in Bounded Treewidth Graphs 2016 ·DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) ·Alina Ene, Matthias Mnich, Marcin Pilipczuk, Andrej Risteski	1
14	A Latent Variable Model Approach to PMI-based Word Embeddings 2016 ·Transactions of the Association for Computational Linguistics ·Sanjeev Arora, Yuanzhi Li, Yingyu Liang, Tengyu Ma, Andrej Risteski	118
15	Recovery Guarantee of Non-negative Matrix Factorization via Alternating Updates 2016 ·arXiv (Cornell University) ·Yuanzhi Li, Yingyu Liang, Andrej Risteski	2
16	Label optimal regret bounds for online local learning 2015 ·Conference on Learning Theory ·Pranjal Awasthi, Moses Charikar, (unknown), Andrej Risteski	1
17	What makes a Tree a Straight Skeleton 2012 ·Oswin Aichholzer, Howard Cheng, Satyan L. Devadoss, Thomas Hackl, Stefan Huber, Brian Li, Andrej Risteski	2

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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