[20] Josef Urban - Deductive and Inductive Reasoning in Large Libraries of Formalized Mathematics

The Thesis Review

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เนื้อหาจัดทำโดย The Thesis Review and Sean Welleck เนื้อหาพอดแคสต์ทั้งหมด รวมถึงตอน กราฟิก และคำอธิบายพอดแคสต์ได้รับการอัปโหลดและจัดหาให้โดยตรงจาก The Thesis Review and Sean Welleck หรือพันธมิตรแพลตฟอร์มพอดแคสต์ของพวกเขา หากคุณเชื่อว่ามีบุคคลอื่นใช้งานที่มีลิขสิทธิ์ของคุณโดยไม่ได้รับอนุญาต คุณสามารถปฏิบัติตามขั้นตอนที่แสดงไว้ที่นี่ https://th.player.fm/legal

Mind The Business: Small Business Success Stories

1
Pushing Past Stagnation & Business Plateaus 30:21

5 วันที่แล้ว30:21

ลิสต์เล่นในภายหลัง

ลิสต์

ถูกใจ

ที่ถูกใจแล้ว

30:21

Hitting plateaus is a common milestone in business, but there’s a difference between stability and a rut. In the last installment of this season, we’ll dive into the ways small business owners push beyond plateaus and find new ways to achieve revenue growth. Jannese and Austin wrap up their time in Nashville, Tennessee with a wonderful visit to N.B. Goods to speak with owner Camille Alston . Camille details the times where she hit a wall with profits, the strategies she implemented to increase revenue, what worked, what didn’t, and the important lessons she learned in the process. You won’t want to miss this informative final chapter! Learn more about how QuickBooks can help you grow your business: QuickBooks.com See omnystudio.com/listener for privacy information.…

4 ปีที่แล้ว 1:25:18

MP3•หน้าโฮมของตอน

Josef Urban is a Principal Researcher at the Czech Institute of Informatics, Robotics, and Cybernetics. His research focuses on artificial intelligence for large-scale computer-assisted reasoning. Josef's PhD thesis is titled "Exploring and Combining Deductive and Inductive Reasoning in Large Libraries of Formalized Mathematics", which he completed in 2004 at Charles University in Prague. We discuss his PhD work on the Mizar Problems for Theorem Proving, machine learning for premise selection, and how it evolved into his recent research. Episode notes: https://cs.nyu.edu/~welleck/episode20.html Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview

49 ตอน

#Science #Thesis Review #Sean Welleck

The Thesis Review

[20] Josef Urban - Deductive and Inductive Reasoning in Large Libraries of Formalized Mathematics

The Thesis Review

published 4 ปีที่แล้ว

แบ่งปัน

MP3•หน้าโฮมของตอน

49 ตอน

#Science #Thesis Review #Sean Welleck

ทุกตอน

The Thesis Review

1
[48] Tianqi Chen - Scalable and Intelligent Learning Systems 46:29

25 weeksที่แล้ว46:29

46:29

Tianqi Chen is an Assistant Professor in the Machine Learning Department and Computer Science Department at Carnegie Mellon University and the Chief Technologist of OctoML. His research focuses on the intersection of machine learning and systems. Tianqi's PhD thesis is titled "Scalable and Intelligent Learning Systems," which he completed in 2019 at the University of Washington. We discuss his influential work on machine learning systems, starting with the development of XGBoost,an optimized distributed gradient boosting library that has had an enormous impact in the field. We also cover his contributions to deep learning frameworks like MXNet and machine learning compilation with TVM, and connect these to modern generative AI. - Episode notes: www.wellecks.com/thesisreview/episode48.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Follow Tianqi Chen on Twitter (@tqchenml) - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview…

The Thesis Review

1
[47] Niloofar Mireshghallah - Auditing and Mitigating Safety Risks in Large Language Models 1:17:06

27 weeksที่แล้ว1:17:06

1:17:06

Niloofar Mireshghallah is a postdoctoral scholar at the University of Washington. Her research focuses on privacy, natural language processing, and the societal implications of machine learning. Niloofar completed her PhD in 2023 at UC San Diego, where she was advised by Taylor Berg-Kirkpatrick. Her PhD thesis is titled "Auditing and Mitigating Safety Risks in Large Language Models." We discuss her journey into research and her work on privacy and LLMs, including how privacy is defined, common attacks and mitigations, differential privacy, and the balance between memorization and generalization. - Episode notes: www.wellecks.com/thesisreview/episode47.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview…

The Thesis Review

1
[46] Yulia Tsvetkov - Linguistic Knowledge in Data-Driven NLP 59:53

2 yearsที่แล้ว59:53

59:53

Yulia Tsvetkov is a Professor in the Allen School of Computer Science & Engineering at the University of Washington. Her research focuses on multilingual NLP, NLP for social good, and language generation. Yulia's PhD thesis is titled "Linguistic Knowledge in Data-Driven Natural Language Processing", which she completed in 2016 at CMU. We discuss getting started in research, then move to Yulia's work in the thesis that combines ideas from linguistics and natural language processing. We discuss low-resource and multilingual NLP, large language models, and great advice about research and beyond. - Episode notes: www.wellecks.com/thesisreview/episode46.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Find out more info about the show at www.wellecks.com/thesisreview - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview…

The Thesis Review

1
[45] Luke Zettlemoyer - Learning to Map Sentences to Logical Form 59:35

2 yearsที่แล้ว59:35

59:35

Luke Zettlemoyer is a Professor at the University of Washington and Research Scientist at Meta. His work spans machine learning and NLP, including foundational work in large-scale self-supervised pretraining of language models. Luke's PhD thesis is titled "Learning to Map Sentences to Logical Form", which he completed in 2009 at MIT. We talk about his PhD work, the path to the foundational Elmo paper, and various topics related to large language models. - Episode notes: www.wellecks.com/thesisreview/episode45.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Find out more info about the show at www.wellecks.com/thesisreview - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview…

The Thesis Review

1
[44] Hady Elsahar - NLG from Structured Knowledge Bases (& Controlling LMs) 1:05:56

3 yearsที่แล้ว1:05:56

1:05:56

Hady Elsahar is a Research Scientist at Naver Labs Europe. His research focuses on Neural Language Generation under constrained and controlled conditions. Hady's PhD was on interactions between Natural Language and Structured Knowledge bases for Data2Text Generation and Relation Extraction & Discovery, which he completed in 2019 at the Université de Lyon. We talk about his phd work and how it led to interests in multilingual and low-resource in NLP, as well as controlled generation. We dive deeper in controlling language models, including his interesting work on distributional control and energy-based models. - Episode notes: www.wellecks.com/thesisreview/episode44.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Find out more info about the show at www.wellecks.com/thesisreview - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview…

The Thesis Review

1
[43] Swarat Chaudhuri - Logics and Algorithms for Software Model Checking 1:06:18

3 yearsที่แล้ว1:06:18

1:06:18

Swarat Chaudhuri is an Associate Professor at the University of Texas. His lab studies problems at the interface of programming languages, logic and formal methods, and machine learning. Swarat's PhD thesis is titled "Logics and Algorithms for Software Model Checking", which he completed in 2007 at the University of Pennsylvania. We discuss reasoning about programs, formal methods & safer machine learning systems, and the future of program synthesis & neurosymbolic programming. - Episode notes: www.wellecks.com/thesisreview/episode43.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Find out more info about the show at www.wellecks.com/thesisreview - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview…

The Thesis Review

1
[42] Charles Sutton - Efficient Training Methods for Conditional Random Fields 1:18:01

3 yearsที่แล้ว1:18:01

1:18:01

Charles Sutton is a Research Scientist at Google Brain and an Associate Professor at the University of Edinburgh. His research focuses on deep learning for generating code and helping people write better programs. Charles' PhD thesis is titled "Efficient Training Methods for Conditional Random Fields", which he completed in 2008 at UMass Amherst. We start with his work in the thesis on structured models for text, and compare/contrast with today's large language models. From there, we discuss machine learning for code & the future of language models in program synthesis. - Episode notes: https://cs.nyu.edu/~welleck/episode42.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview…

The Thesis Review

1
[41] Talia Ringer - Proof Repair 1:19:02

3 yearsที่แล้ว1:19:02

1:19:02

Talia Ringer is an Assistant Professor with the Programming Languages, Formal Methods, and Software Engineering group at University of Illinois Urbana-Champaign. Her research focuses on formal verification and proof engineering technologies. Talia's PhD thesis is titled "Proof Repair", which she completed in 2021 at the University of Washington. We discuss software verification and her PhD work on proof repair for maintaining verified systems, and discuss the intersection of machine learning with her work. - Episode notes: https://cs.nyu.edu/~welleck/episode41.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview…

The Thesis Review

1
[40] Lisa Lee - Learning Embodied Agents with Scalably-Supervised RL 46:59

3 yearsที่แล้ว46:59

46:59

Lisa Lee is a Research Scientist at Google Brain. Her research focuses on building AI agents that can learn and adapt like humans and animals do. Lisa's PhD thesis is titled "Learning Embodied Agents with Scalably-Supervised Reinforcement Learning", which she completed in 2021 at Carnegie Mellon University. We talk about her work in the thesis on reinforcement learning, including exploration, learning with weak supervision, and embodied agents, and cover various topics related to trends in reinforcement learning. - Episode notes: https://cs.nyu.edu/~welleck/episode40.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview…

The Thesis Review

1
[39] Burr Settles - Curious Machines: Active Learning with Structured Instances 1:06:33

3 yearsที่แล้ว1:06:33

1:06:33

Burr Settles leads the research group at Duolingo, a language-learning website and mobile app whose mission is to make language education free and accessible to everyone. Burr’s PhD thesis is titled "Curious Machines: Active Learning with Structured Instances", which he completed in 2008 at the University of Wisconsin-Madison. We talk about his work in the thesis on active learning, then chart the path to Burr’s role at DuoLingo. We discuss machine learning for education and language learning, including content, assessment, and the exciting possibilities opened by recent advancements. - Episode notes: https://cs.nyu.edu/~welleck/episode39.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview…

The Thesis Review

1
[38] Andrew Lampinen - A Computational Framework for Learning and Transforming Task Representations 1:04:47

3 yearsที่แล้ว1:04:47

1:04:47

Andrew Lampinen is a research scientist at DeepMind. His research focuses on cognitive flexibility and generalization. Andrew’s PhD thesis is titled "A Computational Framework for Learning and Transforming Task Representations", which he completed in 2020 at Stanford University. We talk about cognitive flexibility in brains and machines, centered around his work in the thesis on meta-mapping. We cover a lot of interesting ground, including complementary learning systems and memory, compositionality and systematicity, and the role of symbols in machine learning. - Episode notes: https://cs.nyu.edu/~welleck/episode38.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview…

The Thesis Review

1
[37] Joonkoo Park - Neural Substrates of Visual Word and Number Processing 1:09:28

3 yearsที่แล้ว1:09:28

1:09:28

Joonkoo Park is an Associate Professor and Honors Faculty in the Department of Psychological and Brain Sciences at UMass Amherst. He leads the Cognitive and Developmental Neuroscience Lab, focusing on understanding the developmental mechanisms and neurocognitive underpinnings of our knowledge about number and mathematics. Joonkoo’s PhD thesis is titled "Experiential Effects on the Neural Substrates of Visual Word and Number Processing", which he completed in 2011 at the University of Michigan. We talk about numerical processing in the brain, starting with nature vs. nurture, including the learned versus built-in aspects of neural architectures. We talk about the difference between word and number processing, types of numerical thinking, and symbolic vs. non-symbolic numerical processing. - Episode notes: https://cs.nyu.edu/~welleck/episode37.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview…

The Thesis Review

1
[36] Dieuwke Hupkes - Hierarchy and Interpretability in Neural Models of Language Processing 1:02:26

3 yearsที่แล้ว1:02:26

1:02:26

Dieuwke Hupkes is a Research Scientist at Facebook AI Research and the scientific manager of the Amsterdam unit of ELLIS. Dieuwke's PhD thesis is titled, "Hierarchy and Interpretability in Neural Models of Language Processing", which she completed in 2020 at the University of Amsterdam. We discuss her work on which aspects of hierarchical compositionality and syntactic structure can be learned by recurrent neural networks, how these models can serve as explanatory models of human language processing, what compositionality actually means, and a lot more. - Episode notes: https://cs.nyu.edu/~welleck/episode36.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview…

The Thesis Review

1
[35] Armando Solar-Lezama - Program Synthesis by Sketching 1:15:56

3 yearsที่แล้ว1:15:56

1:15:56

Armando Solar-Lezama is a Professor at MIT, and the Associate Director & COO of CSAIL. He leads the Computer Assisted Programming Group, focused on program synthesis. Armando’s PhD thesis is titled, "Program Synthesis by Sketching", which he completed in 2008 at UC Berkeley. We talk about program synthesis & his work on Sketch, how machine learning's role in program synthesis has evolved over time, and more. - Episode notes: https://cs.nyu.edu/~welleck/episode35.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview…

The Thesis Review

1
[34] Sasha Rush - Lagrangian Relaxation for Natural Language Decoding 1:08:12

4 yearsที่แล้ว1:08:12

1:08:12

Sasha Rush is an Associate Professor at Cornell Tech and researcher at Hugging Face. His research focuses on building NLP systems that are safe, fast, and controllable. Sasha's PhD thesis is titled, "Lagrangian Relaxation for Natural Language Decoding", which he completed in 2014 at MIT. We talk about his work in the thesis on decoding in NLP, how it connects with today, and many interesting topics along the way such as the role of engineering in machine learning, breadth vs. depth, and more. - Episode notes: https://cs.nyu.edu/~welleck/episode34.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview…

The Thesis Review

1
[18] Eero Simoncelli - Distributed Representation and Analysis of Visual Motion 1:25:37

4 yearsที่แล้ว1:25:37

1:25:37

Eero Simoncelli is a Professor of Neural Science, Mathematics, Data Science, and Psychology at New York University. His research focuses on representation and analysis of visual information. Eero's PhD thesis is titled "Distributed Representation & Analysis of Visual Motion", which he completed in 1993 at MIT. We discuss his PhD work which focused on optical flow, which ideas and methods have stayed with him throughout his career, making biological connections with machine learning models, and how Eero's perspective of vision has evolved. Episode notes: https://cs.nyu.edu/~welleck/episode18.html Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview…

The Thesis Review

1
[17] Paul Middlebrooks - Neuronal Correlates of Meta-Cognition in Primate Frontal Cortex 1:36:10

4 yearsที่แล้ว1:36:10

1:36:10

Paul Middlebrooks is a neuroscientist and host of the Brain Inspired podcast, which explores the intersection of neuroscience and artificial intelligence. Paul's PhD thesis is titled "Neuronal Correlates of Meta-Cognition in Primate Frontal Cortex", which he completed at the University of Pittsburgh in 2011. We discuss Paul's work on meta-cognition - informally, thinking about thinking - then discuss neuroscience for A.I. and A.I. for neuroscience. Episode notes: https://cs.nyu.edu/~welleck/episode17.html Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html Support The Thesis Review at https://www.patreon.com/thesisreview…

The Thesis Review

1
[16] Aaron Courville - A Latent Cause Theory of Classical Conditioning 1:19:21

4 yearsที่แล้ว1:19:21

1:19:21

Aaron Courville is a Professor at the University of Montreal. His research focuses on the development of deep learning models and methods. Aaron's PhD thesis is titled "A Latent Cause Theory of Classical Conditioning", which he completed at Carnegie Mellon University in 2006. We discuss Aaron's work on the latent cause theory during his PhD, talk about how Aaron moved into machine learning and deep learning research, chart a path to today's deep learning methods, and discuss his recent work on systematic generalization in language. Episode notes: cs.nyu.edu/~welleck/episode16.html Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html Support The Thesis Review at www.buymeacoffee.com/thesisreview…

The Thesis Review

1
[15] Christian Szegedy - Some Applications of the Weighted Combinatorial Laplacian 1:06:52

4 yearsที่แล้ว1:06:52

1:06:52

Christian Szegedy is a Research Scientist at Google. His research machine learning methods such as the inception architecture, batch normalization and adversarial examples, and he currently investigates machine learning for mathematical reasoning. Christian’s PhD thesis is titled "Some Applications of the Weighted Combinatorial Laplacian" which he completed in 2005 at the University of Bonn. We discuss Christian’s background in mathematics, his PhD work on areas of both pure and applied mathematics, and his path into machine learning research. Finally, we discuss his recent work with using deep learning for mathematical reasoning and automatically formalizing mathematics. Episode notes: https://cs.nyu.edu/~welleck/episode15.html Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html Support The Thesis Review at www.buymeacoffee.com/thesisreview…

The Thesis Review

1
[14] Been Kim - Interactive and Interpretable Machine Learning Models 1:04:22

4 yearsที่แล้ว1:04:22

1:04:22

Been Kim is a Research Scientist at Google Brain. Her research focuses on designing high-performance machine learning methods that make sense to humans. Been's PhD thesis is titled "Interactive and Interpretable Machine Learning Models for Human Machine Collaboration", which she completed in 2015 at MIT. We discuss her work on interpretability, including her work in the thesis on the Bayesian Case Model and its interactive version, as well as connections with her subsequent work on black-box interpretability methods that are used in many real-world applications. Episode notes: https://cs.nyu.edu/~welleck/episode14.html Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html Support The Thesis Review at www.buymeacoffee.com/thesisreview…

The Thesis Review

1
[13] Adji Bousso Dieng - Deep Probabilistic Graphical Modeling 1:07:50

4 yearsที่แล้ว1:07:50

1:07:50

Adji Bousso Dieng is currently a Research Scientist at Google AI, and will be starting as an assistant professor at Princeton University in 2021. Her research focuses on combining probabilistic graphical modeling and deep learning to design models for structured high-dimensional data. Her PhD thesis is titled "Deep Probabilistic Graphical Modeling", which she completed in 2020 at Columbia University. We discuss her work on combining graphical models and deep learning, including models and algorithms, the value of interpretability and probabilistic models, as well as applications and making an impact through research. Episode notes: https://cs.nyu.edu/~welleck/episode13.html Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html Support The Thesis Review at www.buymeacoffee.com/thesisreview…

The Thesis Review

1
[12] Martha White - Regularized Factor Models 1:08:35

4 yearsที่แล้ว1:08:35

1:08:35

Martha White is an Associate Professor at the University of Alberta. Her research focuses on developing reinforcement learning and representation learning techniques for adaptive, autonomous agents learning on streams of data. Her PhD thesis is titled "Regularized Factor Models", which she completed in 2014 at the University of Alberta. We discuss the regularized factor model framework, which unifies many machine learning methods and led to new algorithms and applications. We talk about sparsity and how it also appears in her later work, as well as the common threads between her thesis work and her research in reinforcement learning. Episode notes: https://cs.nyu.edu/~welleck/episode12.html Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html Support The Thesis Review at www.buymeacoffee.com/thesisreview…

The Thesis Review

1
[11] Jacob Andreas - Learning from Language 1:19:43

4 yearsที่แล้ว1:19:43

1:19:43

Jacob Andreas is an Assistant Professor at MIT, where he leads the language and intelligence group, focusing on language as a communicative and computational tool. His PhD thesis is titled "Learning from Language" which he completed in 2018 at UC Berkeley. We discuss compositionality and neural module networks, the intersection of RL and language, and translating a neural communication channel called 'neuralese', and how this can lead to more interpretable machine learning models. Episode notes: https://cs.nyu.edu/~welleck/episode11.html Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html Support The Thesis Review at www.buymeacoffee.com/thesisreview…

The Thesis Review

1
[10] Chelsea Finn - Learning to Learn with Gradients 51:44

5 yearsที่แล้ว51:44

51:44

Chelsea Finn is an Assistant Professor at Stanford University, where she leads the IRIS lab that studies intelligence through robotic interaction at scale. Her PhD thesis is titled "Learning to Learn with Gradients", which she completed in 2018 at UC Berkeley. Chelsea received the prestigious ACM Doctoral Dissertation Award for her work in the thesis. We discuss machine learning for robotics, focusing on learning-to-learn - also known as meta-learning - and her work on the MAML algorithm during her PhD, as well as the future of robotics research. Episode notes: https://cs.nyu.edu/~welleck/episode10.html Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html Support The Thesis Review at www.buymeacoffee.com/thesisreview…

The Thesis Review

1
[09] Kenneth Stanley - Efficient Evolution of Neural Networks through Complexification 1:21:26

5 yearsที่แล้ว1:21:26

1:21:26

Kenneth Stanley is a researcher at OpenAI, where he leads the team on Open-endedness. Previously he was a Professor Computer Science at the University of Central Florida, cofounder of Geometric Intelligence, and head of Core AI research at Uber AI labs. His PhD thesis is titled "Efficient Evolution of Neural Networks through Complexification", which he completed on 2004 at the University of Texas. We talk about evolving increasingly complex structures and how this led to the NEAT algorithm that he developed during his PhD. We discuss his research directions related to open-endedness, how the field has changed over time, and how he currently views algorithms that were developed over a decade ago. Episode notes: https://cs.nyu.edu/~welleck/episode9.html Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html Support The Thesis Review at www.buymeacoffee.com/thesisreview…

The Thesis Review

1
[08] He He - Sequential Decisions and Predictions in NLP 1:00:39

5 yearsที่แล้ว1:00:39

1:00:39

He He is an Assistant Professor at New York University. Her research focuses on enabling reliable communication in natural language between machine and humans, including topics in text generation, robust language understanding, and dialogue systems. Her PhD thesis is titled "Sequential Decisions and Predictions in NLP", which she completed in 2016 at the University of Maryland. We talk about the intersection of language with imitation learning and reinforcement learning, her work in the thesis on opponent modeling and simultaneous translation, and how it relates to recent work on generation and robustness. Episode notes: https://cs.nyu.edu/~welleck/episode8.html Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html Support The Thesis Review at www.buymeacoffee.com/thesisreview…

The Thesis Review

1
[07] John Schulman - Optimizing Expectations: From Deep RL to Stochastic Computation Graphs 1:04:28

5 yearsที่แล้ว1:04:28

1:04:28

John Schulman is a Research Scientist and co-founder of Open AI. John co-leads the reinforcement learning team, researching algorithms that safely and efficiently learn by trial and error and by imitating humans. His PhD thesis is titled "Optimizing Expectations: From Deep Reinforcement Learning to Stochastic Computation Graphs", which he completed in 2016 at Berkeley. We talk about his work on stochastic computation graphs and TRPO, how it evolved to PPO and how it's used in large-scale applications like Open AI Five, as well as his recent work on generalization in RL. Episode notes: https://cs.nyu.edu/~welleck/episode7.html Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html Support The Thesis Review at www.buymeacoffee.com/thesisreview…

The Thesis Review

1
[06] Yoon Kim - Deep Latent Variable Models of Natural Language 1:05:50

5 yearsที่แล้ว1:05:50

1:05:50

Yoon Kim is currently a Research Scientist at the MIT-IBM AI Watson Lab, and will be joining MIT as an assistant professor in 2021. Yoon’s research focuses on machine learning and natural language processing. His PhD thesis is titled "Deep Latent Variable Models of Natural Language", which he completed in 2020 at Harvard University. We discuss his work on uncovering latent structure in natural language, including continuous vector representations, tree structures, and grammars. We cover learning and variational inference methods that he developed during his PhD, and he offers a look at where latent variable models will be heading in the future. Episode notes: https://cs.nyu.edu/~welleck/episode6.html Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html Support The Thesis Review at www.buymeacoffee.com/thesisreview…

The Thesis Review

1
[05] Julian Togelius - Computational Intelligence and Games 1:12:06

5 yearsที่แล้ว1:12:06

1:12:06

Julian Togelius is an Associate Professor at New York University, where he co-directs the NYU Game Innovation Lab. His research is at the intersection of computational intelligence and computer games. His PhD thesis is titled "Optimization, Imitation, and Innovation: Computational Intelligence and Games", which he completed in 2007. We cover his work in the thesis on AI for games and games for AI, and how it connects to his recent work on procedural content generation. Episode notes: https://cs.nyu.edu/~welleck/episode5.html Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html Support The Thesis Review at https://www.buymeacoffee.com/thesisreview…

The Thesis Review

1
[04] Sebastian Nowozin - Learning with Structured Data: Applications to Computer Vision 1:44:32

5 yearsที่แล้ว1:44:32

1:44:32

Sebastian Nowozin is currently a Researcher at Microsoft Research Cambridge. His research focuses on probabilistic deep learning, consequences of model misspecification, understanding agent complexity in order to improve learning efficiency, and designing models for reasoning and planning. His PhD thesis is titled "Learning with Structured Data: Applications to Computer Vision", which he completed in 2009. We discuss the work in his thesis on structured inputs and structured outputs, which involves beautiful ideas from polyhedral combinatorics and optimization. We talk about his recent work on Bayesian deep learning and the connections it has to ideas that he explored during his PhD. Episode notes: https://cs.nyu.edu/~welleck/episode4.html Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html…

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The Thesis Review « » [20] Josef Urban - Deductive and Inductive Reasoning in Large Libraries of Formalized Mathematics

[20] Josef Urban - Deductive and Inductive Reasoning in Large Libraries of Formalized Mathematics

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[20] Josef Urban - Deductive and Inductive Reasoning in Large Libraries of Formalized Mathematics