arXiv research

Study on teaching complexity in graphs, proving hardness and tractability.

New method stops experiments early for harm in diverse groups.

We describe two nonconventional algorithms for linear regression, called GAME and CLASH. The salient characteristics of these approaches is that they exploit the convex $\ell_1$-ball and non-convex $\ell_0$-sparsity constraints jointly in sparse recovery. To establish the theoretical approximation guarantees of GAME an…

Algorithmic machine teaching studies the interaction between a teacher and a learner where the teacher selects labeled examples aiming at teaching a target hypothesis. In a quest to lower teaching complexity and to achieve more natural teacher-learner interactions, several teaching models and complexity measures have b…

Formal models of learning from teachers need to respect certain criteria to avoid collusion. The most commonly accepted notion of collusion-freeness was proposed by Goldman and Mathias (1996), and various teaching models obeying their criterion have been studied. For each model $M$ and each concept class $\mathcal{C}$,…

This paper modifies the Ait-Sahalia model to better describe interest rate behaviors.

This work tackles continual learning with semi-supervised data, showing that even with minimal labeled data, performance can match full-supervised methods.

The fashion industry is establishing its presence on a number of visual-centric social media like Instagram. This creates an interesting clash as fashion brands that have traditionally practiced highly creative and editorialized image marketing now have to engage with people on the platform that epitomizes impromptu, r…

Deep learning faces adoption challenges in business analytics.

Novel framework for teaching complexity in machine teaching models.

Artificial Intelligence (AI), defined in its most simple form, is a technological tool that makes machines intelligent. Since learning is at the core of intelligence, machine learning poses itself as a core sub-field of AI. Then there comes a subclass of machine learning, known as deep learning, to address the limitati…

DiAMoNDBack models protein backmapping from coarse-grained Cα traces.

Deep CNNs diagnose chest X-rays for COVID-19 and other pneumonia.