Все публикации

'Personalized Medicine Based

'Personalized Medicine Based on Deep Human Phenotyping' - Eran Segal

'Efficient “Curriculum-Based” Training'

'Efficient “Curriculum-Based” Training' - Abhishek Panigrahi, Young Researcher Seminar Series

'White-Box Transformers via

'White-Box Transformers via Sparse Rate Reduction' - Sam Buchanan, Research at TTIC

'How Should We

'How Should We Tokenize Visual Data?' - Greg Shakhnarovich, Research at TTIC

'Reinforcement Learning for

'Reinforcement Learning for Reasoning in Large Language Models with One Training Example' - Simon Du

'Improving the Diversity

'Improving the Diversity and Evaluation of Large Models' - Richard Zemel, TTIC

'From Raw Waveform

'From Raw Waveform to Spectrum: Advances in Diffusion Models for Speech Generation' - Joseph Keshet

'Intellectual Property and

'Intellectual Property and the Research Ecosystem' - Matthew Turk, Research at TTIC

'Dynamics of Concept

'Dynamics of Concept Learning and Emergent Abilities in Neural Networks' - Ekdeep Lubana

'Deep Networks as

'Deep Networks as Convex Models: Exact Lasso Formulations via Geometric Algebra' - Mert Pilanci

'Understanding Large Vision

'Understanding Large Vision Models' - Antonio Torralba, TTIC Distinguished Lecture Series

'Verifying Classification with

'Verifying Classification with Limited Disclosure' - Siddharth Bhandari, Research at TTIC

Provable Tuning of

Provable Tuning of Deep Learning Model Hyperparameters - Dravyansh Sharma, Talks at TTIC

'Fully Dynamic Algorithms

'Fully Dynamic Algorithms for Graph Spanners via Low-Diameter Router Decomposition' - Julia Chuzhoy

'Space Complexity of

'Space Complexity of Minimum Cut Problems in Single-Pass Streams' - Vihan Shah, Young Researcher

'Learning Mechanics of

'Learning Mechanics of Neural Networks' - Daniel Kunin, Young Researcher Series Seminar

'From Scalars to

'From Scalars to Vectors: Approximability and Hardness of ℓₚ-Shortest Path' - Yury Makarychev

'Machine Learning from

'Machine Learning from Weak, Noisy, and Biased Supervision' - Masashi Sugiyama, TTIC Colloquium

'Computing Small Volume

'Computing Small Volume Confidence Set for Arbitrary Distribution' - Liren Shan, Research at TTIC

Local-to-global Theorems On

Local-to-global Theorems On High Dimensional Expanders - Irit Dinur, Distinguished Lecture Series

'Near-optimal Regret in

'Near-optimal Regret in Online MDPs with Aggregate Bandit Feedback' - Tal Lancewicki, Research TTIC

'Expander Graphs and

'Expander Graphs and Optimally List-Decodable Codes'- Madhur Tulsiani, Research at TTIC

'Safe and Reasonable

'Safe and Reasonable AI' - Avi Schwarzschild, Talks at TTIC

'Pencil: Long Thoughts

'Pencil: Long Thoughts with Short Memory' - Zhiyuan Li, Research at TTIC

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