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Algorithms Lab
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A lab that studies machine learning and data mining from both theoretical and applied perspectives.
AboutAbout the lab
Learning algorithms, from both theory and application.
The Algorithms Lab studies algorithms in machine learning and data mining from both theoretical and applied perspectives.
On the theory side, it covers online learning, in which the next action is decided while receiving the results of past actions, and active learning, which reaches an answer with few queries.
On the applied side, it works on learning from information obtained on the Web, learners that run on limited hardware, and applications to biology and medicine.
The lab aims to formulate real-world problems and build algorithms with performance guarantees.
Key terms
- Online learning
- A learning framework that repeatedly decides the next action while receiving actions and their results, in order to maximize the total gain
- Active learning
- Learning in which the learner itself chooses and fetches the data needed to improve accuracy. It can learn from less data
- Data mining
- Techniques for extracting useful rules and patterns from large amounts of data
NewsLab news
A paper by Prof. Nakamura et al. was published in Machine Learning
An undergraduate student received the Student Presentation Award at DEIM2026
ResearchResearch themes
The lab studies machine learning and data mining from both theoretical and applied perspectives. On the theory side, it examines the mechanisms of learning itself; on the applied side, it addresses their use on the Web, in hardware, and in biology and medicine.
*Illustrative imageOnline learning
This is learning that repeatedly decides the next action based on past actions and their gains and losses, in order to maximize the total gain. The lab studies algorithms with performance guarantees, and the limits of performance, in various settings with different information constraints and objective functions.
*Illustrative imageActive learning
This is a theory that pursues what to ask in order to find the answer with few queries. Unlike learning that receives data drawn from a fixed distribution, the learner successively fetches the data needed to improve accuracy at that point, so it can learn from less data.
*Illustrative imageWeb mining
The lab learns from behavior logs and sensor information obtained instantly through the Web, and uses it for recommending ads and products suited to each person and for detecting fraud. Online learning, which updates hypotheses with sequentially arriving data, and active learning, which improves accuracy, both play a major role.
*Illustrative imageApplications to hardware design
Machine learning uses a lot of computation, so it requires high-performance machines and cannot be used on edge devices with limited computing resources. The lab develops techniques for learning small classifiers and predictors that run on limited hardware.
MembersFaculty
The members of the Algorithms Lab consist of faculty, and doctoral, master's, and undergraduate students.As of 2026
- ProfessorAtsuyoshi Nakamura
- Associate ProfessorDai Hai Nguyen
VoicesStudent voices
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Sorting shellsort anim” Simpsons contributor / CC0 (cropped)
- Online learning: “Chess pieces close up” Aaaatu / CC BY-SA 4.0 (cropped)
- Active learning: “Fork in the forest road - geograph.org.uk - 7687024” Alec MacKinnon / CC BY-SA 2.0 (cropped)
- Web mining: “Ethernet Patch Panel” Kbh3rd / CC BY 4.0 (cropped)
- Applications to hardware design: “RedPitaya STEMLab FPGA v1.1 topview” Geek3 / CC BY-SA 4.0 (cropped)
- Related lab (Information Knowledge Network Lab): “Code on computer monitor (Unsplash)” Markus Spiske markusspiske / CC0 (cropped)
- Related lab (Large-Scale Knowledge Processing Lab): “Network Visualization” Martin Grandjean / CC BY-SA 4.0 (cropped)
- Related lab (High Performance Computing Lab): “CSCS Supercomputer Alps 1” Marco Abram, CSCS / CC BY-SA 3.0 (cropped)
- Related lab (Information Analysis Lab): “Dilution Fridge with Quantum Processors Enclosed 008 8K” OJB Quantum / CC BY 4.0 (cropped)
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