Demo Data from EDBT 2026 / reviewers in the wild / expert
Samuel P. M. Choi
dblp:61/6060 · also Samuel Ping-Man Choi
· DBLP profile ↗
4ranked-venue papers
3as first author
0since 2021 · last 2005
0000-0002-7180-0801ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2 · 2 first-authorComputer networks · 1 · 1 first-authorApplied, interdisciplinary, general and emerging computing · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Artificial intelligence
2 papers |
Reinforcement learning · 83% Robot navigation and mapping · 17% | |
| Computer networks
1 paper |
Routing and switching · 77% Internet architecture and protocols · 23% |
Topics — the 10 heaviest of 10, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Reinforcement learning › model-based reinforcement learning
environment model |
0.0 | 1 | 1999 | An Environment Model for Nonstationary Reinforcement Learning · NIPS 1999 |
Robotics › Robot navigation and mapping › robot mapping
environment modeling |
0.0 | 1 | 1999 | An Environment Model for Nonstationary Reinforcement Learning · NIPS 1999 |
Machine learning › Reinforcement learning
model-based reinforcement learning |
0.0 | 1 | 1999 | An Environment Model for Nonstationary Reinforcement Learning · NIPS 1999 |
Machine learning › Reinforcement learning
non-stationary reinforcement learning |
0.0 | 1 | 1999 | An Environment Model for Nonstationary Reinforcement Learning · NIPS 1999 |
Machine learning › Reinforcement learning › value-based reinforcement learning
q-learning |
0.0 | 1 | 1995 | Predictive Q-Routing: A Memory-based Reinforcement Learning Approach to Adaptive Traffic Control · NIPS 1995 |
Machine learning › Reinforcement learning
value-based reinforcement learning |
0.0 | 1 | 1995 | Predictive Q-Routing: A Memory-based Reinforcement Learning Approach to Adaptive Traffic Control · NIPS 1995 |
Routing and switching
adaptive routing |
0.0 | 1 | 1995 | Predictive Q-Routing: A Memory-based Reinforcement Learning Approach to Adaptive Traffic Control · NIPS 1995 |
Machine learning › Reinforcement learning
markov decision process |
0.0 | 1 | 1999 | An Environment Model for Nonstationary Reinforcement Learning · NIPS 1999 |
Machine learning › Reinforcement learning › markov decision process
non-stationary MDP |
0.0 | 1 | 1999 | An Environment Model for Nonstationary Reinforcement Learning · NIPS 1999 |
Internet architecture and protocols › traffic management
traffic control |
0.0 | 1 | 1995 | Predictive Q-Routing: A Memory-based Reinforcement Learning Approach to Adaptive Traffic Control · NIPS 1995 |
Methods — techniques the papers use, named apart from their topics
reinforcement learning · 0.0memory-based learning · 0.0environment model learning · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2005 | Towards end-to-end privacy control in the outsourcing of marketing activities: a web service integration solutionabstractWith the recent adoption of marketing activities outsourcing, there have been increasing demands and concerns for privacy control. The traditional approach of a bulk transmission of the customers' information to a marketing company cannot meet such demands, especially in the finance and healthcare businesses. Therefore, we propose a layered architecture and a development methodology for end-to-end privacy control over the export of each individual customer's records through a Web services platform, according to the corresponding enterprise's privacy control policies. A Web services system, with up-dated security and privacy facilities, can provide a suitable interoperation platform for required application-to-application interactions over the Internet. We further develop a conceptual model and an interaction protocol to send only the required part of a customer's records at a time. We illustrate our approach for end-to-end privacy control with a tele-marketing case study and show how the software of the outsourced call center can be integrated effectively with the Web services of a bank to protect privacy. Copyright 2005 ACM. Patrick C. K. Hung, Dickson K. W. Chiu, W. W. Fung, William Kwok-Wai Cheung, Raymond K. Wong 0001, Samuel P. M. Choi, Eleanna Kafeza, James T. Kwok, Joshua C. C. Pun, Vivying S. Y. Cheng |
ICEC | 6 |
| 2001 | A genetic agent-based negotiation system
Samuel P. M. Choi, Jiming Liu 0001, Sheung-Ping Chan |
Comput. Networks | 1 |
| 1999 | An Environment Model for Nonstationary Reinforcement Learning
Samuel P. M. Choi, Dit-Yan Yeung, Nevin Lianwen Zhang |
NIPS | 1 |
| 1995 | Predictive Q-Routing: A Memory-based Reinforcement Learning Approach to Adaptive Traffic Control
Samuel P. M. Choi, Dit-Yan Yeung |
NIPS | 1 |