Alec Koppel

1.5k total citations
76 papers, 787 citations indexed

About

Alec Koppel is a scholar working on Artificial Intelligence, Computer Networks and Communications and Computational Mechanics. According to data from OpenAlex, Alec Koppel has authored 76 papers receiving a total of 787 indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Artificial Intelligence, 36 papers in Computer Networks and Communications and 25 papers in Computational Mechanics. Recurrent topics in Alec Koppel's work include Sparse and Compressive Sensing Techniques (25 papers), Advanced Bandit Algorithms Research (23 papers) and Distributed Control Multi-Agent Systems (21 papers). Alec Koppel is often cited by papers focused on Sparse and Compressive Sensing Techniques (25 papers), Advanced Bandit Algorithms Research (23 papers) and Distributed Control Multi-Agent Systems (21 papers). Alec Koppel collaborates with scholars based in United States, India and Netherlands. Alec Koppel's co-authors include Alejandro Ribeiro, Amrit Singh Bedi, Aryan Mokhtari, Ketan Rajawat, Brian M. Sadler, Geert Leus, Andrea Simonetto, Kaiqing Zhang, Tamer Başar and Hao Zhu and has published in prestigious journals such as IEEE Transactions on Automatic Control, IEEE Transactions on Signal Processing and IEEE Signal Processing Magazine.

In The Last Decade

Alec Koppel

70 papers receiving 771 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alec Koppel United States 14 365 353 203 192 152 76 787
Ketan Rajawat India 17 290 0.8× 220 0.6× 80 0.4× 154 0.8× 336 2.2× 98 728
Deming Yuan China 23 1.2k 3.3× 320 0.9× 167 0.8× 208 1.1× 198 1.3× 68 1.4k
Davood Hajinezhad United States 10 205 0.6× 240 0.7× 37 0.2× 159 0.8× 77 0.5× 12 565
Qingguo Lü China 14 522 1.4× 220 0.6× 41 0.2× 92 0.5× 191 1.3× 55 744
Mark Eisen United States 16 475 1.3× 314 0.9× 32 0.2× 65 0.3× 495 3.3× 52 1.0k
Pham Dinh Tao France 5 85 0.2× 106 0.3× 50 0.2× 176 0.9× 116 0.8× 7 600
Michel Vasquez France 12 422 1.2× 129 0.4× 47 0.2× 95 0.5× 84 0.6× 24 796
Euhanna Ghadimi Sweden 13 530 1.5× 118 0.3× 21 0.1× 77 0.4× 388 2.6× 23 805
Takashi Tanaka United States 15 290 0.8× 185 0.5× 41 0.2× 21 0.1× 154 1.0× 83 840
Spyridon D. Mourtas Greece 15 42 0.1× 291 0.8× 163 0.8× 69 0.4× 52 0.3× 57 669

Countries citing papers authored by Alec Koppel

Since Specialization
Citations

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

Fields of papers citing papers by Alec Koppel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alec Koppel

This figure shows the co-authorship network connecting the top 25 collaborators of Alec Koppel. A scholar is included among the top collaborators of Alec Koppel 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 Alec Koppel. Alec Koppel 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
1.
Koppel, Alec, et al.. (2024). Occupancy Information Ratio: Infinite-Horizon, Information-Directed, Parameterized Policy Search. SIAM Journal on Control and Optimization. 62(6). 3145–3171.
2.
Bedi, Amrit Singh, et al.. (2023). Dealing with Sparse Rewards in Continuous Control Robotics via Heavy-Tailed Policy Optimization. 989–995. 2 indexed citations
3.
Koppel, Alec, et al.. (2023). On the sample complexity of actor-critic method for reinforcement learning with function approximation. Machine Learning. 112(7). 2433–2467. 21 indexed citations
4.
Bedi, Amrit Singh, Pratap Tokekar, Alec Koppel, et al.. (2023). Posterior Coreset Construction with Kernelized Stein Discrepancy for Model-Based Reinforcement Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 37(6). 6980–6988. 2 indexed citations
5.
6.
Rajawat, Ketan, et al.. (2022). Sparse Representations of Positive Functions via First- and Second-Order Pseudo-Mirror Descent. IEEE Transactions on Signal Processing. 70. 3148–3164. 2 indexed citations
7.
Bedi, Amrit Singh, et al.. (2022). Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Primal-Dual Approach. Proceedings of the AAAI Conference on Artificial Intelligence. 36(4). 3682–3689. 12 indexed citations
8.
Bedi, Amrit Singh, Alec Koppel, Ketan Rajawat, et al.. (2021). Dynamic Online Learning via Frank-Wolfe Algorithm. IEEE Transactions on Signal Processing. 69. 932–947. 11 indexed citations
9.
Koppel, Alec, et al.. (2021). Collaborative Beamforming for Agents with Localization Errors. 2021 55th Asilomar Conference on Signals, Systems, and Computers. 204–208. 2 indexed citations
10.
Zhang, Kaiqing, Alec Koppel, Hao Zhu, & Tamer Başar. (2019). Convergence and Iteration Complexity of Policy Gradient Method for Infinite-horizon Reinforcement Learning. 7415–7422. 4 indexed citations
11.
Koppel, Alec, Amrit Singh Bedi, Brian M. Sadler, & V́ıctor Elvira. (2019). Nearly Consistent Finite Particle Estimates in Streaming Importance\n Sampling. arXiv (Cornell University). 1 indexed citations
12.
Koppel, Alec, Kaiqing Zhang, Hao Zhu, & Tamer Başar. (2019). Projected Stochastic Primal-Dual Method for Constrained Online Learning With Kernels. IEEE Transactions on Signal Processing. 67(10). 2528–2542. 9 indexed citations
13.
Koppel, Alec. (2019). Consistent Online Gaussian Process Regression Without the Sample Complexity Bottleneck. 3512–3518. 11 indexed citations
14.
Jalaian, Brian, et al.. (2018). On Stream-Centric Learning for Internet of Battlefield Things.. National Conference on Artificial Intelligence. 1 indexed citations
15.
Koppel, Alec, Santiago Paternain, Cédric Richard, & Alejandro Ribeiro. (2018). Decentralized Online Learning With Kernels. IEEE Transactions on Signal Processing. 66(12). 3240–3255. 38 indexed citations
16.
Koppel, Alec, Aryan Mokhtari, & Alejandro Ribeiro. (2018). Parallel Stochastic Successive Convex Approximation Method for Large-Scale Dictionary Learning. 2771–2775. 9 indexed citations
17.
Zhang, Kaiqing, Hao Zhu, Tamer Başar, & Alec Koppel. (2018). Projected Stochastic Primal-Dual Method for Constrained Online Learning with Kernels. 52. 4224–4231. 2 indexed citations
18.
Bedi, Amrit Singh, Alec Koppel, & Ketan Rajawat. (2017). Beyond Consensus and Synchrony in Online Network Optimization via Saddle Point Method. arXiv (Cornell University). 2 indexed citations
19.
Bedi, Amrit Singh, Alec Koppel, & Ketan Rajawat. (2017). Beyond consensus and synchrony in decentralized online optimization using saddle point method. 293–297. 10 indexed citations
20.
Koppel, Alec, Jonathan Fink, Garrett Warnell, Ethan Stump, & Alejandro Ribeiro. (2016). Online learning for characterizing unknown environments in ground robotic vehicle models. 626–633. 10 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.

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