Amit Daniely

1.1k total citations
22 papers, 231 citations indexed

About

Amit Daniely is a scholar working on Artificial Intelligence, Management Science and Operations Research and Computer Networks and Communications. According to data from OpenAlex, Amit Daniely has authored 22 papers receiving a total of 231 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Artificial Intelligence, 5 papers in Management Science and Operations Research and 4 papers in Computer Networks and Communications. Recurrent topics in Amit Daniely's work include Machine Learning and Algorithms (10 papers), Imbalanced Data Classification Techniques (5 papers) and Optimization and Search Problems (4 papers). Amit Daniely is often cited by papers focused on Machine Learning and Algorithms (10 papers), Imbalanced Data Classification Techniques (5 papers) and Optimization and Search Problems (4 papers). Amit Daniely collaborates with scholars based in Israel, United States and Canada. Amit Daniely's co-authors include Shai Shalev‐Shwartz, Nati Linial, Yoram Singer, Sivan Sabato, Roy Frostig, Michael Schapira, Shai Ben-David, Michael Saks, Yonatan Bilu and Nevena Lazic and has published in prestigious journals such as The Journal of Chemical Physics, The Journal of Physical Chemistry A and Journal of Machine Learning Research.

In The Last Decade

Amit Daniely

21 papers receiving 211 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Amit Daniely Israel	9	182	55	44	39	26	22	231
Abbas Mehrabian Canada	9	124 0.7×	48 0.9×	68 1.5×	29 0.7×	35 1.3×	27	258
Paul F. Christiano United States	5	116 0.6×	17 0.3×	79 1.8×	42 1.1×	24 0.9×	8	210
Tasuku Soma Japan	7	62 0.3×	21 0.4×	100 2.3×	62 1.6×	8 0.3×	15	169
Alistair Stewart United States	6	109 0.6×	21 0.4×	29 0.7×	21 0.5×	12 0.5×	21	178
Mariane Pelletier France	9	178 1.0×	51 0.9×	20 0.5×	50 1.3×	9 0.3×	25	296
Omri Weinstein United States	8	111 0.6×	27 0.5×	136 3.1×	40 1.0×	14 0.5×	32	196
Thomas Dueholm Hansen Denmark	7	94 0.5×	22 0.4×	108 2.5×	40 1.0×	8 0.3×	21	187
Gottlieb Pirsic Austria	9	57 0.3×	21 0.4×	28 0.6×	11 0.3×	54 2.1×	22	191
Michael Capalbo United States	9	97 0.5×	28 0.5×	163 3.7×	72 1.8×	6 0.2×	16	286
Pieter C. Allaart United States	8	31 0.2×	29 0.5×	61 1.4×	13 0.3×	10 0.4×	36	192

Countries citing papers authored by Amit Daniely

Since Specialization

Citations

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

Fields of papers citing papers by Amit Daniely

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Amit Daniely

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Daniely, Amit, Helen R. Eisenberg, Ester Livshits, et al.. (2025). Photochemical pathways in astronomical ices: A computational study of singlet oxygen reactions with hydrocarbons. The Journal of Chemical Physics. 162(1). 2 indexed citations

Daniely, Amit, et al.. (2024). A Vacuum Ultraviolet Photoionization Mass Spectrometry and Density Functional Calculation Study of Formic Acid–Water Clusters. The Journal of Physical Chemistry A. 128(31). 6392–6401. 1 indexed citations

Shalev‐Shwartz, Shai, et al.. (2020). The Implicit Bias of Depth: How Incremental Learning Drives Generalization. International Conference on Learning Representations. 3 indexed citations

Daniely, Amit & Yishay Mansour. (2019). Competitive ratio vs regret minimization: achieving the best of both worlds.. 333–368. 1 indexed citations

Daniely, Amit, et al.. (2019). Generalization Bounds for Neural Networks via Approximate Description Length. arXiv (Cornell University). 32. 12988–12996. 2 indexed citations

Daniely, Amit, et al.. (2018). Inapproximability of Truthful Mechanisms via Generalizations of the Vapnik--Chervonenkis Dimension. SIAM Journal on Computing. 47(1). 96–120.

Daniely, Amit, Nevena Lazic, Yoram Singer, & Kunal Talwar. (2017). Short and Deep: Sketching and Neural Networks. International Conference on Learning Representations. 2 indexed citations

Daniely, Amit. (2017). Depth Separation for Neural Networks. arXiv (Cornell University). 690–696. 3 indexed citations

Daniely, Amit. (2017). SGD Learns the Conjugate Kernel Class of the Network. arXiv (Cornell University). 17 indexed citations

10.

Daniely, Amit & Shai Shalev‐Shwartz. (2016). Complexity Theoretic Limitations on Learning DNF’s. Conference on Learning Theory. 815–830. 6 indexed citations

11.

Daniely, Amit, Roy Frostig, & Yoram Singer. (2016). Toward Deeper Understanding of Neural Networks: The Power of Initialization and a Dual View on Expressivity. Neural Information Processing Systems. 29. 2253–2261. 23 indexed citations

12.

Daniely, Amit. (2016). Complexity theoretic limitations on learning halfspaces. 105–117. 20 indexed citations

13.

Daniely, Amit, et al.. (2015). Strongly Adaptive Online Learning. International Conference on Machine Learning. 1405–1411. 23 indexed citations

14.

Daniely, Amit & Shai Shalev‐Shwartz. (2014). Optimal Learners for Multiclass Problems. arXiv (Cornell University). 287–316. 17 indexed citations

15.

Daniely, Amit, Nati Linial, & Shai Shalev‐Shwartz. (2014). From average case complexity to improper learning complexity. 441–448. 35 indexed citations

16.

Daniely, Amit, et al.. (2013). The price of bandit information in multiclass online classification. Conference on Learning Theory. 93–104. 1 indexed citations

17.

Daniely, Amit, Sivan Sabato, Shai Ben-David, & Shai Shalev‐Shwartz. (2013). Multiclass learnability and the ERM principle. Journal of Machine Learning Research. 16(1). 207–232. 22 indexed citations

18.

Daniely, Amit, Nati Linial, & Shai Shalev‐Shwartz. (2013). More data speeds up training time in learning halfspaces over sparse vectors. arXiv (Cornell University). 26. 145–153. 19 indexed citations

19.

Bilu, Yonatan, Amit Daniely, Nati Linial, & Michael Saks. (2013). On the practically interesting instances of MAXCUT. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 8 indexed citations

20.

Daniely, Amit, et al.. (2012). Multiclass Learning Approaches: A Theoretical Comparison with Implications. arXiv (Cornell University). 25. 485–493. 8 indexed citations

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.

Explore authors with similar magnitude of impact