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An Exposition of Pathfinding Strategies Within Lightning Network Clients

The Lightning Network is a peer-to-peer network designed to address Bitcoin’s scalability challenges, facilitating rapid, cost-effective, and instantaneous transactions through bidirectional, blockchain-backed payment channels among network peers. …

Sparse Recovery for Overcomplete Frames: Sensing Matrices and Recovery Guarantees

Signal models formed as linear combinations of few atoms from an over-complete dictionary or few frame vectors from a redundant frame have become central to many applications in high dimensional signal processing and data analysis. A core question …

Fibottention: Inceptive Visual Representation Learning with Diverse Attention Across Heads

Visual perception tasks are predominantly solved by Vision Transformer (ViT) architectures, which, despite their effectiveness, encounter a computational bottleneck due to the quadratic complexity of computing self-attention. This inefficiency is …

UnitNorm: Rethinking Normalization for Transformers in Time Series

Normalization techniques are crucial for enhancing Transformer models’ performance and stability in time series analysis tasks, yet traditional methods like batch and layer normalization often lead to issues such as token shift, attention shift, and …

A Quotient Property for Matrices with Heavy-Tailed Entries and its Application to Noise-Blind Compressed Sensing

For a large class of random matrices $A$ with i.i.d. entries we show that the $\ell_1$-quotient property holds with probability exponentially close to $1$. In contrast to previous results, our analysis does not require concentration of the entrywise …