4 papers · 1 filter
Linear Regression with Unknown Truncation Beyond Gaussian Features
Alexandros Kouridakis, Anay Mehrotra, Alkis Kalavasis +1
In truncated linear regression, samples are shown only when the outcome falls inside a certain survival set and the goal is to estimate the unknown -dimens…
MaxSketch: Robust Distinct Counting in Streams via Random Projections
Nikos Tsikouras, Constantine Caramanis, Christos Tzamos
Estimating the number of distinct elements in a data stream is well understood when repeated elements are identical. In modern settings, however, observations are high-dimensional…
On Mitigating Affinity Bias through Bandits with Evolving Biased Feedback
Matthew Faw, Constantine Caramanis, Jessica Hoffmann
Unconscious bias has been shown to influence how we assess our peers, with consequences for hiring, promotions and admissions. In this work, we focus on affinity bias, the componen…
Optimization Can Learn Johnson Lindenstrauss Embeddings
Nikos Tsikouras, Constantine Caramanis, Christos Tzamos
Embeddings play a pivotal role across various disciplines, offering compact representations of complex data structures. Randomized methods like Johnson-Lindenstrauss (JL) provide s…