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LecturesTuesdays 10:15am-12:00pm in BC 010
Web Pagehttp://parsa.epfl.ch/courses/cs723/
InstructorBabak Falsafi
Email, URLbabak.falsafi /at/ epfl.ch, http://parsa.epfl.ch/~falsafi
OfficeINJ 233
Phone+41 21 69 35592
InstructorMartin Jaggi
Email, URLmartin.jaggi /at/ epfl.ch, http://people.epfl.ch/martin.jaggi
OfficeINJ 341
InstructorAnne-Marie Kermarrec
Email, URLanne-marie.kermarrec /at/ epfl.ch, http://people.epfl.ch/anne-marie.kermarrec
OfficeBC 162
Phone+41 21 69 31297
Admin. AssistantStephanie Baillargues
Emailstephanie.baillargues /at/ epfl.ch
OfficeINJ 234

Topics in Machine Learning Systems

The course will cover recent papers from the literature in the emerging area of ML systems. With the emergence of massive data and data science, machine learning is widely applicable in a variety of usage scenarios with high performance, accuracy and cost being key design goals. The latter not only has implications for algorithms but also platforms from software to hardware to enable collective optimization of the design metrics. The topic is inherently multidisciplinary and will cover papers from a variety of conferences in computer science subfields. Students will understand the state-of-the-art in the emerging area of ML Systems. Specifically, the course will cover core technologies in production ML systems including:
  1. languages and paradigms for specification of large-scaling machine learning applications,
  2. the convergence of analytics from relational databases to unstructured data,
  3. resource management in large-scaling ML systems,
  4. network stacks for ML systems,
  5. emerging ML systems accelerator architecture.

Who should take CS 723?

CS 723 is a graduate course and is highly recommended for master and PhD students. Like other graduate-level courses, the course includes weekly readings, discussions, and questions on papers of seminal and recent contributions to the field of systems for machine learning.

Readings and Presentations

In this course, we will read papers, and take turn presenting them. It is absolutely important to read the papers prior to attending class because the class will proceed in the form of a discussion among participants and a presentation to introduce the main topics covered in the papers. The students will take turn presenting throughout the semester.

Attendance

You are expected to be in the classroom and actively participate in the discussions.

Prerequisites

Graduate level course in computer architecture, programming languages, and/or systems

Submission System

Submit your write-ups to cs723-grading@groupes.epfl.ch before noon on Mondays.

Grading

The students will be graded based on class discussions, presentations and short reviews written for each reading assignment.