A type of artificial intelligence that focuses on designing systems that can learn from and make decisions based on data.
This academic article, titled ‘Uncovering Meanings of Embeddings via Partial Orthogonality’, delves into how machine learning tools encode the semantic structure of language in text embeddings. The authors specifically study…
Continue readingThe paper presents a novel method called Geometric Harmonization (GH) to address the issue of representation learning disparity in self-supervised learning (SSL), particularly under long-tailed distribution scenarios. Traditional SSL methods…
Continue readingThe paper presents a novel approach to generative models, extending the continuous time framework from Brownian motion to fractional Brownian motion (FBM). The authors propose Generative Fractional Diffusion Models (GFDM),…
Continue readingThe article focuses on the issue of adversarial attacks in machine learning, particularly transfer attacks. The authors argue that traditional white-box threat models are unrealistic and introduce a new practical…
Continue readingThe article ‘High-Dimensional Prediction for Sequential Decision Making’ by Georgy Noarov et al. explores the problem of making predictions for a high-dimensional state chosen by an adversary. The predictions are…
Continue readingThe research paper investigates the possibility of transferring ‘complementary’ knowledge between any arbitrary pairing of pretrained models, without any performance degradation. The authors found that each model learns unique feature…
Continue readingThis paper examines the influence of detect-and-remove defenses, ILP and LGS, on optical flow methods. Adversarial patches, placed in arbitrary scene locations, can undermine the reliability of optical flow predictions….
Continue readingThe study focuses on the issue of automatic sign language recognition, specifically Argentinian Sign Language (LSA), using a technique called ProbSom. The complexity of this issue lies in its multidisciplinary…
Continue readingThis research paper focuses on Automatic Sign Language Recognition (SLR), a complex, multidisciplinary field that combines video processing, machine learning, and linguistics. The authors present a model for sign classification…
Continue readingThis paper presents a new method for 3D object localization using only 2D labels and the physical laws of motion. No 3D labels or expensive hardware is needed. The model…
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