Protein sequence optimization under tight oracle budgets requires methods that explore vast combinatorial spaces while making each evaluation informative. Existing reinforcement learning and off-polic...
Financial crashes, cascading failures in infrastructure, and critical errors in AI systems are frequently triggered by events that occur with extremely small probability. Efficiently discovering and s...
Let $G_{n,p}$ be the binomial random graph of density $p$ and let $X_H$ be the number of copies of a fixed graph $H$ in $G_{n,p}$. We prove asymptotically tight bounds on the logarithmic upper-tail pr...
Speculative decoding accelerates large language model (LLM) inference by using a small draft model to propose candidate tokens that a larger target model verifies. A critical hyperparameter in this pr...
Calibration is a conditional property that depends on the information retained by a predictor. We develop decomposition identities for arbitrary proper losses that make this dependence explicit. At an...
Autonomous marine pollution-monitoring platforms must operate for extended periods in remote, harsh sea environments with limited maintenance access, making power-source selection a critical design ch...
Data increasingly arrive as collections of curves - a voice recording, a growth trajectory, a day of sensor readings - where each observation is a whole function rather than a single number. The usual...
In Poisson Boolean models with deterministic ball grains, the directional visible range from an uncovered point is known to be exponentially distributed in Euclidean and real hyperbolic space. We show...
Loss functions play a central role in supervised classification. Cross-entropy (CE) is widely used, whereas the mean absolute error (MAE) loss can offer robustness but is difficult to optimize. Interp...
Legal disputes unfold through sequences of filings in which parties update their positions and may settle at any stage. Most computational studies of legal prediction, however, focus on adjudicated ou...
The equilibrium between hydrated and hydrolysed forms of CO2 in water is central to a multitude of processes in geology, oceanography and biology. Chemistry of the carbonate system is well understood ...
We introduce EntroPath, a manifold learning method that recovers geodesic geometry from data graphs through ensembles of diffusion paths. Many existing graph-based embeddings rely either on locally no...
Depth of anesthesia is a complex but important vital state to analyze during a surgery or other procedure. One parameter to estimate this state is the bispectral index (BIS), a value ranging from 0 to...
We apply ordinal-pattern analysis and permutation entropy (PE) to satellite-derived chlorophyll-a (Chl-a), sea surface temperature (SST), and mixed-layer depth (MLD) data to investigate the spatiotemp...
We derive explicit lower bounds for relative Fisher information by combining a variational principle with suitably orthogonalized Hermite-polynomial test functions. The resulting cumulant bounds are a...
Linear Independent Component Analysis (ICA) recovers jointly independent source signals from their linear mixtures. To achieve this, classical ICA algorithms attempt to maximize non-Gaussianity, measu...
Artificial transaction generation remains an important source of potential market manipulation on cryptocurrency exchanges, as it may distort reported liquidity and reduce market transparency. This st...
Passive models for long video understanding typically rely on a "watch-it-all" paradigm, processing frames uniformly regardless of query difficulty, causing computational cost to grow with video durat...
Conservative offline training is widely advocated as a safe foundation for subsequent online adaptation: if a policy stays close to well-supported behaviour, the argument goes, it is less likely to ex...
The paper introduces an infinite integer sequence progression that produces a triangular array for which the $n$th row sums to $2^n$ for every $n\geq0$. Every row of the triangular array can be realiz...
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