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Investment professionals rely on extrapolating company revenue into the future (i.e. revenue forecast) to approximate the valuation of scaleups (private companies in a high-growth stage) and inform their investment decision. This task is manual and ...

Representing dynamic textures (DTs) plays an important role in many real implementations in the computer vision community. Due to the turbulent and non-directional motions of DTs along with the negative impacts of different factors (e.g., environmental ...

Recent progress in reinforcement learning has led to remarkable performance in a range of applications, but its deployment in high-stakes settings remains quite rare. One reason is a limited understanding of the behavior of reinforcement algorithms, both ...

A practically significant effect of a surge occurrences in linear dynamical systems under nonzero initial conditions is explored. The linear dynamical system subjected to unknown-but-bounded exogenous disturbances is considered. Using the ...

In the proposed random communication system (RCS), the alpha‐stable (α‐stable) noise as a random carrier drives the transmitter which is modelled by the linear dynamical system and the skewness parameter of the random carrier encodes the binary messages. ...

We investigate model order reduction (MOR) for linear dynamical systems, where a quadratic output is defined as a quantity of interest. The system can be transformed into a linear dynamical system with many linear outputs. MOR is feasible by the method of ...

We prove that stochastic gradient descent efficiently converges to the global optimizer of the maximum likelihood objective of an unknown linear time-invariant dynamical system from a sequence of noisy observations generated by the system. Even though ...

Generation of natural human motion is one of key techniques for multimodal dialogue systems with a human-like avatar. In particular, natural and expressive lip motion synthesis is necessary to make conversation between a user and an avatar richer. ...

The dynamic texture clustering over space and time, which considers a video as a sample from a linear dynamical system, has recently received great attention. While there exist many algorithms for time-varying characteristics and phenomena clustering, ...

The efficacy of many Body Sensor Network (BSN) applications relies on the accurate temporal clustering of human motion into actions on various time scales. This is typically done with the use of inertial sensors and processing algorithms that try to ...

Physical activity monitoring in free-living populations has many applications for public health research, weight-loss interventions, context-aware recommendation systems and assistive technologies. We present a system for physical activity recognition ...

Dynamic textures are sequences of images of moving scenes in time that are common in natural scenes and play an important role in video content analysis. This paper presents a new dynamic Bayesian framework for segmentation of dynamic textures. First, ...

Compressive sensing (CS) enables the acquisition and recovery of sparse signals and images at sampling rates significantly below the classical Nyquist rate. Despite significant progress in the theory and methods of CS, little headway has been made in ...

Real world applications such as hands-free dialling in cars may have to deal with potentially very noisy environments. Existing state-of-the-art solutions to this problem use feature-based HMMs, with a preprocessing stage to clean the noisy signal. ...

A standard approach to model reduction of large-scale higher-order linear dynamical systems is to rewrite the system as an equivalent first-order system and then employ Krylov-subspace techniques for model reduction of first-order systems. This ...