Summer Graduate School on Mathematics for Machine Learning | (smr 4222) (15-26 June 2026)

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Contribution List

Displaying 40 contributions out of 40

Problem Session lead by TAs and lecturers

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Problem Session lead by TAs and lecturers

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Problem Session lead by TAs and lecturers

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Problem Session lead by TAs and lecturers

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Problem Session lead by TAs and lecturers

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Problem Session lead by TAs and lecturers

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Problem Session lead by TAs and lecturers

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Problem Session lead by TAs and lecturers

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Problem Session lead by TAs and lecturers

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Problem Session lead by TAs and lecturers

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Problem Session lead by lecturers and teaching assistants

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Problem Session lead by lecturers and teaching assistants

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Problem Session lead by lecturers and teaching assistants

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Problem Session lead by lecturers and teaching assistants

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Problem Session lead by lecturers and teaching assistants

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Problem Session lead by lecturers and teaching assistants

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Problem Session lead by lecturers and teaching assistants

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Problem Session lead by lecturers and teaching assistants

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Problem Session lead by lecturers and teaching assistants

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Problem Session lead by lecturers and teaching assistants

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Rigorous approaches to modern machine learning - session 1

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Rigorous approaches to modern machine learning - session 10

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Rigorous approaches to modern machine learning - session 2

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Rigorous approaches to modern machine learning - session 3

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Rigorous approaches to modern machine learning - session 4

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Rigorous approaches to modern machine learning - session 5

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Rigorous approaches to modern machine learning - session 6

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Rigorous approaches to modern machine learning - session 7

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Rigorous approaches to modern machine learning - session 8

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Rigorous approaches to modern machine learning - session 9

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Statistical physics approach to high-dimensional learning problems - session 1

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Statistical physics approach to high-dimensional learning problems - session 10

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Statistical physics approach to high-dimensional learning problems - session 2

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Statistical physics approach to high-dimensional learning problems - session 3

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Statistical physics approach to high-dimensional learning problems - session 4

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Statistical physics approach to high-dimensional learning problems - session 5

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Statistical physics approach to high-dimensional learning problems - session 6

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Statistical physics approach to high-dimensional learning problems - session 7

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Statistical physics approach to high-dimensional learning problems - session 8

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Statistical physics approach to high-dimensional learning problems - session 9

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Organizers

Claudio Arezzo (ICTP), Jean Barbier (ICTP), Filippo Bracci (Rome Tor Vergata and INdAM), Domenico Marinucci (Rome Tor Vergata and INdAM), Cristina Trombetti (Napoli Federico II and INdAM), Local Organiser: Jean Barbier (ICTP)

Co-sponsors

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