paperium.hashnode.devSparse Networks from Scratch: Faster Training without Losing PerformanceSparse Momentum: Framing and Aims Context and scientific motivation At first glance this work situates itself within sparse model training by proposing a strategy to keep networks sparse throughout training while aiming to match dense accuracy, which...11m ago·4 min read
paperium.hashnode.devMachine learning \& artificial intelligence in the quantum domainQuantum-classical convergence: scope and framing Context and objectives At first glance, the intersection of information theory and learning looks like two independent revolutions slowly colliding; in practice, the literature shows a deliberate fusio...1h ago·5 min read
paperium.hashnode.devA Convex Framework for Fair RegressionA convex framework for fairness-aware regression Scope and framing At first glance the work synthesizes a compact optimization viewpoint: it proposes a family of convex fairness regularizers that plug into standard linear and logistic regression loss...2h ago·4 min read
paperium.hashnode.devUncovering the Limits of Adversarial Training against Norm-Bounded AdversarialExamplesUnderstanding the Practical Limits of Adversarial Training Context and high-level goal At first glance, the field of robust learning appears to have converged on a small set of effective tools, yet this work re-examines that assumption and pushes the...3h ago·5 min read
paperium.hashnode.devRelation Classification via Recurrent Neural NetworkTemporal Modeling versus Local Pattern Learning Motivation and framing At first glance the field has favored convolutional architectures for sentence-level relation detection, yet a persistent concern appears to be their limited handling of sequentia...4h ago·3 min read
