Adaptivity in Machine Learning with Samory Kpotufe - #512
2021-08-23 · 50 min · episode 512 · 16 entities
Asserted relationships
-
→ appeared on The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence podcast0.68
evidence rules-v4
Adaptivity in Machine Learning with Samory Kpotufe - #512
-
0.55
evidence rules-v4
Feed author/publisher: Sam Charrington
-
0.50
evidence rules-v4
professor at Columbia University and
-
0.50
evidence rules-v4
professor at Columbia University and
-
0.40
evidence rules-v4
Feed category: Science
-
0.40
evidence rules-v4
Feed category: Technology
-
0.40
evidence rules-v4
Feed category: News
-
0.40
evidence rules-v4
Feed category: Tech News
-
0.40
evidence rules-v4
Feed author/publisher: TWIML
Entities found in this episode
companys 7
-
0.70
evidence rules-v4
Feed author/publisher: TWIML
-
0.62
evidence rules-v4
professor at Columbia University and
-
0.50
evidence rules-v4
Feed category: Technology
-
0.50
evidence rules-v4
professor at Columbia University and
-
0.50
evidence rules-v4
professor at Columbia University and
-
0.40
evidence rules-v4
Feed category: Technology
-
0.40
evidence rules-v4
Feed author/publisher: TWIML
concepts 5
-
0.50
evidence rules-v4
Feed category: Science
-
0.50
evidence rules-v4
Feed category: Tech News
-
0.40
evidence rules-v4
Feed category: Science
-
0.40
evidence rules-v4
Feed category: News
-
0.40
evidence rules-v4
Feed category: Tech News
persons 3
-
0.72
evidence rules-v4
Adaptivity in Machine Learning with Samory Kpotufe - #512
-
0.70
evidence rules-v4
Feed author/publisher: Sam Charrington
-
0.55
evidence rules-v4
Feed author/publisher: Sam Charrington
podcasts 1
-
appeared on The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence podcast0.68
evidence rules-v4
Adaptivity in Machine Learning with Samory Kpotufe - #512
Episode description as stored
Today we’re joined by Samory Kpotufe, an associate professor at Columbia University and program chair of the 2021 Conference on Learning Theory (COLT).
In our conversation with Samory, we explore his research at the intersection of machine learning, statistics, and learning theory, and his goal of reaching self-tuning, adaptive algorithms. We discuss Samory’s research in transfer learning and other potential procedures that could positively affect transfer, as well as his work understanding unsupervised learning including how clustering could be applied to real-world applications like cybersecurity, IoT (Smart homes, smart city sensors, etc) using methods like dimension reduction, random projection, and others. If you enjoyed this interview, you should definitely check out our conversation with Jelani Nelson on the “Theory of Computation.”
The complete show notes for this episode can be found at https://twimlai.com/go/512.