Talk “Evaluating ML: When Will We Stop Fooling Ourselves?”

📅 Tuesday, April 21 | 11:00 am

ML Evaluation is usually based on an average measure of success such as accuracy. This kind of evaluation has several drawbacks: (1) the model works well for easy instances but badly for difficult ones, but the actual real distribution is usually not known; (2) this assumes that all errors have the same impact, which is almost never true; and (3) optimizing success does not minimize critical errors. In this presentation we discuss these problems and give some solutions that address them.

Speaker: Ricardo Baeza-Yates, academic at DCC UChile and senior researcher at IMFD.

Location
Ramón Picarte Auditorium
Faculty of Physical and Mathematical Sciences
Universidad de Chile

Address
Beauchef 851, north building, 3rd floor
See map

Event date
April 21, 2026
11:00 am – 12:30 pm

Organizer Department of Computer Science contacto@dcc.uchile.cl

— DCC Communications