arXiv research

SPADE improves demand forecasting accuracy by 4.5% for post-promotion periods.

PEAK tests means of multiple data streams with sequential betting.

Populations of species in ecosystems are often constrained by availability of resources within their environment. In effect this means that a growth of one population, needs to be balanced by comparable reduction in populations of others. In neutral models of biodiversity all populations are assumed to change increment…

This paper explains why double descent sometimes occurs weakly or not at all from an optimization perspective.

We propose a greedy mixture reduction algorithm which is capable of pruning mixture components as well as merging them based on the Kullback-Leibler divergence (KLD). The algorithm is distinct from the well-known Runnalls' KLD based method since it is not restricted to merging operations. The capability of pruning (in …

We introduce novel communication strategies in synchronous distributed Deep Learning consisting of decentralized gradient reduction orchestration and computational graph-aware grouping of gradient tensors. These new techniques produce an optimal overlap between computation and communication and result in near-linear sc…

A robust method for decomposing spectral peaks robust to distortion and interference.

We find empirically a characteristic sharp peak-flat trough pattern in a large set of commodity prices. We argue that the sharp peak structure reflects an endogenous inter-market organization, and that peaks may be seen as local ``singularities'' resulting from imitation and herding. These findings impose a novel strin…

We investigate the statistical properties of the EBS order book for the EUR/USD and USD/JPY currency pairs and the impact of a ten-fold tick size reduction on its dynamics. A large fraction of limit orders are still placed right at or halfway between the old allowed prices. This generates price barriers where the best …

Joint peak detection is a central problem when comparing samples in genomic data analysis, but current algorithms for this task are unsupervised and limited to at most 2 sample types. We propose PeakSegJoint, a new constrained maximum likelihood segmentation model for any number of sample types. To select the number of…

Mass spectrometry (MS) is an important technique for chemical profiling which calculates for a sample a high dimensional histogram-like spectrum. A crucial step of MS data processing is the peak picking which selects peaks containing information about molecules with high concentrations which are of interest in an MS in…

Study on-chain peak shaving to reduce Ethereum transaction costs.

The paper explains two distinct peaks in generalization error for neural networks and simpler models, each governed by different factors.

The heuristic identification of peaks from noisy complex spectra often leads to misunderstanding of the physical and chemical properties of matter. In this paper, we propose a framework based on Bayesian inference, which enables us to separate multipeak spectra into single peaks statistically and consists of two steps.…

Method finds compatible features for subsets of data.

Bayesian framework integrates spectral deconvolution with expert reasoning for robust peak estimation.

FLOPART solves peak detection by creating accurate train and test set predictions.

The paper shows how the generalization curve can have multiple peaks, influenced by data and learning algorithm biases.

PEAKS selects key training examples incrementally based on prediction error and kernel similarity.

Wireless traffic prediction is a fundamental enabler to proactive network optimisation in beyond 5G. Forecasting extreme demand spikes and troughs due to traffic mobility is essential to avoiding outages and improving energy efficiency. Current state-of-the-art deep learning forecasting methods predominantly focus on o…

Data analysis in high-dimensional spaces aims at obtaining a synthetic description of a data set, revealing its main structure and its salient features. We here introduce an approach providing this description in the form of a topography of the data, namely a human-readable chart of the probability density from which t…

LLMs learn peaked distributions slowly due to power-law losses.

Finite-time queue peaks in stochastic networks have logarithmic scaling after geometric thresholds.

Bayesian Quadrature improves ensembling for neural networks with dispersed likelihood peaks.

During a stock market peak the price of a given stock ($i$) jumps from an initial level $p_1(i)$ to a peak level $p_2(i)$ before falling back to a bottom level $p_3(i)$. The ratios $A(i) = p_2(i)/p_1(i)$ and $B(i)= p_3(i)/p_1(i)$ are referred to as the peak- and bottom-amplitude respectively. The paper show…

We present K-Means Batch Bayesian Optimization (KMBBO), a novel batch sampling algorithm for Bayesian Optimization (BO). KMBBO uses unsupervised learning to efficiently estimate peaks of the model acquisition function. We show in empirical experiments that our method outperforms the current state-of-the-art batch alloc…

In this paper, the fractional order curvature equation $(-Δ)^γu = (1 + \varepsilon K(x))u^{\frac{N + 2γ}{N - 2γ}}$ in $\mathbb{R}^N$ is considered. Assuming $K(x)$ has two critical points satisfying certain local conditions, we prove the existence of two-peak solutions.

A nonparametric method for time series analysis extracts envelopes, detects peaks, and clusters data.

Beam search improves UQ in LLMs by reducing duplicates and variance.

Optimizes sampling in continuous domains by adjusting search distribution.

We propose a deep-learning approach based on generative adversarial networks (GANs) to reduce noise in weak lensing mass maps under realistic conditions. We apply image-to-image translation using conditional GANs to the mass map obtained from the first-year data of Subaru Hyper Suprime-Cam (HSC) survey. We train the co…

Recomputation algorithms collectively refer to a family of methods that aims to reduce the memory consumption of the backpropagation by selectively discarding the intermediate results of the forward propagation and recomputing the discarded results as needed. In this paper, we will propose a novel and efficient recompu…

Paper proposes a network framework for prosumers to manage peak loads in Iran.

Traditionally in regression one minimizes the number of fitting parameters or uses smoothing/regularization to trade training (TE) and generalization error (GE). Driving TE to zero by increasing fitting degrees of freedom (dof) is expected to increase GE. However modern big-data approaches, including deep nets, seem to…

New algorithm tackles constrained Markov decision processes with peak constraints.

We win EVA2025 by estimating extreme precipitation events using Peaks Over Thresholds and martingale testing.

Support Vector Data Description (SVDD) provides a useful approach to construct a description of multivariate data for single-class classification and outlier detection with various practical applications. Gaussian kernel used in SVDD formulation allows flexible data description defined by observations designated as sup…

A new clustering algorithm reduces density peaks clustering's computational complexity.

Serenity optimizes neural network execution for edge devices by scheduling with optimal memory footprint.

Paper proposes combining GAM and DNN for accurate peak demand estimation from lower-resolution data.

We study the dynamics of order flows around large intraday price changes using ultra-high-frequency data from the Shenzhen Stock Exchange. We find a significant reversal of price for both intraday price decreases and increases with a permanent price impact. The volatility, the volume of different types of orders, the b…

Efficiently identifies promising hyperparameters for online learning models.

Improved peak detection in ChIP-seq data reduces over-dispersion.

Develops statistical framework for analyzing functional data extremes.

TERA method speeds up derivative Gaussian processes in high dimensions.

New model improves volatility forecasting by reducing overestimation and underestimation.

Extracts important peaks from XRD spectra using Attention mechanism.

During a speculative episode the price of an item jumps from an initial level p_1 to a peak level p_2 before more or less returning to level p_1. The ratio p_2/p_1 is referred to as the amplitude A of the peak. This paper shows that for a given market the peak amplitude is a linear function of the logarithm of the pric…