Fall 2026

Theoretical Foundations of Machine Learning

Advanced mathematical theory and methods of machine learning, covering statistical learning theory, model selection, and optimization.

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Recorded instructors · Fall 2026 No instructors listed

Summary

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Recent recorded grades — Fall 2023: 3.86 GPA, 100.0% A/AB (n=22 letter grades); Fall 2024: 3.86 GPA, 95.2% A/AB (n=21 letter grades); Fall 2025: 3.69 GPA, 83.3% A/AB (n=24 letter grades).

Grade history

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average GPA
letter grades
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Prerequisites

Course map

E C E/​COMP SCI 761 or E C E 830

COMPSCI/ECE/STAT 861

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Professors

Fall 2026

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Calendar & sections

Fall 2026

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Student experience

the class

Recent recorded grades — Fall 2023: 3.86 GPA, 100.0% A/AB (n=22 letter grades); Fall 2024: 3.86 GPA, 95.2% A/AB (n=21 letter grades); Fall 2025: 3.69 GPA, 83.3% A/AB (n=24 letter grades).

difficulty & workload

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Topics

  • Statistical learning theory and Vapnik-Chevronenkis Theory
  • High-dimensional models and nonparametric methods

Skills

  • Statistical learning theory and model selection
  • Probabilistic analysis and optimization

Grades

Latest available · Fall 2025— not enough history to project Fall 2026.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

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AB
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BC
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F

Grades over time

Through Fall 2025

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Sources & history

UW–Madison

Catalog & offerings

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Dataset & model

Recorded 2026-09-07

View the dataset on Hugging Face
Model outputs & technical records
nvidia/Qwen3.6-35B-A3B-NVFP4
LLM outputs across runs
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Full model traces

Recorded model configuration, reasoning, and tool conversations.

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Model & dataset provenance 
{
  "model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
  "model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
  "task_version": "14",
  "output_id": "b5bdcf8058facfd526596c913e9d0b5546ca1918c26eb15f03aeeca6f29a88cb",
  "requirements_status": "needs_review",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}