Andre Wibisono

957 citations
14 papers · 335 · h-index 7

Impact in

Papers in

Andre Wibisono

11 papers receiving 318 citations

Peers

Andre Wibisono
Comparison fields: 5 of 43
  • Artificial Intelligence 233
  • Management Science and Operations Research 83
  • Statistics and Probability 46
  • Computational Mechanics 96
  • Numerical Analysis 24
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Citations per field
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Citations per year

Countries citing papers authored by Andre Wibisono

Since Specialization
Citations

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

Fields of papers citing papers by Andre Wibisono

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 18 scholars most cited alongside Andre Wibisono, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Andre Wibisono Line = papers co-authored together Andre Wibisono links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 2015208
2 201366
3 202312
4
Finite Sample Convergence Rates of Zero-Order Stochastic Optimization Methods
201212
5 201710
6 20127
7
Sufficient Conditions for Uniform Stability of Regularization Algorithms
20096
8 20196
9
Learning and Invariance in a Family of Hierarchical Kernels
20104
10
How to Hedge an Option Against an Adversary: Black-Scholes Pricing is Minimax Optimal
20133
11
Last-Iterate Convergence Rates for Min-Max Optimization: Convergence of Hamiltonian Gradient Descent and Consensus Optimization.
20211
12
Accelerating Rescaled Gradient Descent: Fast Optimization of Smooth Functions
20190
13 20150
14 20220

About Andre Wibisono

Andre Wibisono is a scholar working on Artificial Intelligence, Computational Mechanics, Management Science and Operations Research, Statistics and Probability and Computer Networks and Communications, having authored 14 papers that have together received 335 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (4 papers), Stochastic Gradient Optimization Techniques (4 papers), Markov Chains and Monte Carlo Methods (3 papers), Advanced Bandit Algorithms Research (3 papers), Machine Learning and Algorithms (2 papers), Statistical Methods and Inference (2 papers), Advanced Thermodynamics and Statistical Mechanics (1 paper) and Point processes and geometric inequalities (1 paper). The work is most often cited by research in Artificial Intelligence (233 citations), Management Science and Operations Research (83 citations), Statistics and Probability (46 citations), Computational Mechanics (96 citations) and Numerical Analysis (24 citations). Andre Wibisono has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Michael I. Jordan, Martin J. Wainwright, John C. Duchi, Nicholas Boyd, Tamara Broderick, Ashia Wilson, Santosh Vempala, Rafael Frongillo, Tomaso Poggio and Varun Jog. Their work appears in journals such as IEEE Transactions on Information Theory, Lecture notes in mathematics, Linear Algebra and its Applications, QUT ePrints (Queensland University of Technology) and Neural Information Processing Systems.

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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