arXiv:2603.22465v1 Announce Type: cross Abstract: Federated Learning (FL) is constrained by the communication and energy limitations of decentralized edge devices. While gradient sparsification via Top-K magnitude pruning effectively reduces the communication payload, it remains inherently energy-agnostic. It assumes all parameter updates incur identical downstream transmission and memory-update costs, ignoring hardware realities. We formalize the pruning process as an energy-constrained projection problem that accounts for the hardware-level disparities between memory-intensive and compute-efficient operations during the post-backpropagation phase. We propose […]

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arXiv:2602.11168v1 Announce Type: new Abstract: (Natural Language Processing) NLP techniques such as text classification and topic discovery are very useful in many application areas including information retrieval, knowledge discovery, policy formulation, and decision-making. However, it remains a challenging problem in cases where the categories are unavailable, difficult to differentiate, or are interrelated. Social analysis with human context is an area that can benefit from text classification, as it relies substantially on text data. The focus of this paper […]

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:::info Astounding Stories of Super-Science April 2004, by Astounding Stories is part of HackerNoon’s Book Blog Post series. You can jump to any chapter in this book here. THE COUNTRY OF THE BLIND – XIX. — THE CRYSTAL EGG. Astounding Stories of Super-Science April 2004: THE COUNTRY OF THE BLIND – XIX. — THE CRYSTAL EGG. By H. G. Wells ::: There was, until a year ago, a little and very grimy-looking shop near Seven Dials, over which, in […]

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arXiv:2303.02566v3 Announce Type: replace Abstract: In various practical situations, matrix factorization methods suffer from poor data quality, such as high data sparsity and low signal-to-noise ratio (SNR). Here, we consider a matrix factorization problem by utilizing auxiliary information, which is massively available in real-world applications, to overcome the challenges caused by poor data quality. Unlike existing methods that mainly rely on simple linear models to combine auxiliary information with the main data matrix, we propose to integrate gradient […]

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arXiv:2602.04994v1 Announce Type: new Abstract: With the deep integration of facial recognition into online banking, identity verification, and other networked services, achieving effective decoupling of identity information from visual representations during image storage and transmission has become a critical challenge for privacy protection. To address this issue, we propose SIDeR, a Semantic decoupling-driven framework for unrestricted face privacy protection. SIDeR decomposes a facial image into a machine-recognizable identity feature vector and a visually perceptible semantic appearance component. By […]

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arXiv:2507.09093v2 Announce Type: replace Abstract: We study convergence in high-probability of SGD-type methods in non-convex optimization and the presence of heavy-tailed noise. To combat the heavy-tailed noise, a general black-box nonlinear framework is considered, subsuming nonlinearities like sign, clipping, normalization and their smooth counterparts. Our first result shows that nonlinear SGD (N-SGD) achieves the rate $widetilde{mathcal{O}}(t^{-1/2})$, for any noise with unbounded moments and a symmetric probability density function (PDF). Crucially, N-SGD has exponentially decaying tails, matching the performance […]

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Prediction markets reported their strongest week, with Kalshi hitting a notional volume of $3.54 billion while Polymarket recorded $2.48 billion; the industry’s combined notional volume crossed $6.5 billion, setting a new overall high, according to DeFi Rate. Image source: DeFi Rate This surge coincides with a positive outlook on the industry by Bank of America Analysts who expect sports-related events contracts to hit $1.1 trillion per year. Bernstein also estimates that total market volumes will reach $240 billion […]

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I am training AI players for a chess-like game which has 3 distinct factions (i.e. different piece sets) and is played on a 9×9 board. The three factions are called Axiom (A), Blades (B), and Clockwork (C). With help from ChatGPT, I have managed to create 6 different AI models, one for each match up (AvA, AvB, AvC, BvB, BvC and CvC), under an Alpha Zero style approach. The structure used (which I broadly understand but largely relied […]

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arXiv:2601.08033v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) are the go-to model for graph data analysis. However, GNNs rely on two key operations – aggregation and update, which can pose challenges for low-latency inference tasks or resource-constrained scenarios. Simple Multi-Layer Perceptrons (MLPs) offer a computationally efficient alternative. Yet, training an MLP in a supervised setting often leads to suboptimal performance. Knowledge Distillation (KD) from a GNN teacher to an MLP student has emerged to bridge this gap. […]

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