A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Proposes Textual Echo Cancellation to improve speech recognition.
A new method suppresses echo more effectively with lower latency.
Jointly reduces echo, reverberation, and noise using neural networks.
Accurate on-device keyword spotting (KWS) with low false accept and false reject rate is crucial to customer experience for far-field voice control of conversational agents. It is particularly challenging to maintain low false reject rate in real world conditions where there is (a) ambient noise from external sources s…
In this article, we derive a new stepsize adaptation for the normalized least mean square algorithm (NLMS) by describing the task of linear acoustic echo cancellation from a Bayesian network perspective. Similar to the well-known Kalman filter equations, we model the acoustic wave propagation from the loudspeaker to th…
Adaptive filters are applied in several electronic and communication devices like smartphones, advanced headphones, DSP chips, smart antenna, and teleconference systems. Also, they have application in many areas such as system identification, channel equalization, noise reduction, echo cancellation, interference cancel…
The paper proposes count echo state networks for forecasting graduate student enrollments.
Echo state networks with random weights can approximate any continuous system.
GANs improve echo frame generation with labeled patches.
Study converts echocardiography views using adversarial models.
New technique halves scan time for multi-echo MR images.
Neuro-inspired recurrent neural network algorithms, such as echo state networks, are computationally lightweight and thereby map well onto untethered devices. The baseline echo state network algorithms are shown to be efficient in solving small-scale spatio-temporal problems. However, they underperform for complex task…
Study analyzes Echo State Network parameters for Rossler attractor dynamics.
Efficient echo state network with explicit memory performs well on benchmark tasks.
Tuna-AI uses ML to predict tuna biomass from oceanography and echo-sounder data.
Compression is at the heart of effective representation learning. However, lossy compression is typically achieved through simple parametric models like Gaussian noise to preserve analytic tractability, and the limitations this imposes on learning are largely unexplored. Further, the Gaussian prior assumptions in model…
New approach speeds up optimization with repeated gradient steps on same batch.
Classifies spherical objects filled with water or air using acoustic echoes and Form Function.
This research unifies concepts of fading memory in RNNs.
Note on new cancellation formulas for manifolds.
Ensemble of MFESNs improves macroeconomic forecasting.
Echo state networks are powerful recurrent neural networks. However, they are often unstable and shaky, making the process of finding an good ESN for a specific dataset quite hard. Obtaining a superb accuracy by using the Echo State Network is a challenging task. We create, develop and implement a family of predictably…
The order submission and cancelation processes are two crucial aspects in the price formation of stocks traded in order-driven markets. We investigate the dynamics of order cancelation by studying the statistical properties of inter-cancelation durations defined as the waiting times between consecutive order cancelatio…
Unified treatment of RC in stochastic and deterministic settings.
This work introduces a tensor-based method to perform supervised classification on spatiotemporal data processed in an echo state network. Typically when performing supervised classification tasks on data processed in an echo state network, the entire collection of hidden layer node states from the training dataset is …
Study modular forms over Γ^0(2) and anomaly cancellation formulas.
CESAR improves wind speed and power forecasting for high-resolution simulations.
Many neural networks use the tanh activation function, however when given a probability distribution as input, the problem of computing the output distribution in neural networks with tanh activation has not yet been addressed. One important example is the initialization of the echo state network in reservoir computing…
Study shows structured reservoirs improve deep ESN performance.
Order cancellation process plays a crucial role in the dynamics of price formation in order-driven stock markets and is important in the construction and validation of computational finance models. Based on the order flow data of 18 liquid stocks traded on the Shenzhen Stock Exchange in 2003, we investigate the empiric…
Discrete return (DR) Laser Detection and Ranging (Ladar) systems provide a series of echoes that reflect from objects in a scene. These can be first, last or multi-echo returns. In contrast, Full-Waveform (FW)-Ladar systems measure the intensity of light reflected from objects continuously over a period of time. In a c…
We give a direct proof of a cancellation formula raised in [7] on the level of differential forms. We also obtain more cancellation formulas for even dimensional Riemannian manifolds with a complex line bundle involved. Relations among these cancellation formulas are discussed.
New proof shows Cohen-Lyndon property for non-metric small-cancellation.
For even dimensional manifolds, we prove some twisted anomaly cancellation formulas which generalize some well-known cancellation formulas. For odd dimensional manifolds, we obtain some modularly invariant characteristic forms by the Chern-Simons transgression and we also get some twisted anomaly cancellation formulas.
ESN models predict intraday stock returns efficiently.
New anomaly cancellation formulas for E8*E8*E8 gauge group.
New anomaly formulas from E8 bundles.
Optical ESNs enable flexible, efficient machine learning with reduced energy.
By studying modular invariance properties of some characteristic forms, we prove some new anomaly cancellation formulas which generalize the Han-Zhang and Han-Liu-Zhang anomaly cancellation formulas
New modular forms for anomaly cancellation formulas on any dimensional manifolds.
Paper proposes a method to estimate intra-observer variability in echocardiography quality assessment.
This paper examines the value of a cancellable European option in a finite time horizon setting. The specifications of this generalized European option allow the seller to cancel the option at any point in time for a fixed penalty paid directly to the holder. Here, we provide an explicit valuation formula for the Europ…
State-space systems generate probabilistic dependencies between inputs and outputs.
R package sentometrics analyzes text sentiment for predictions.
Order submission and cancellation are two constituent actions of stock trading behaviors in order-driven markets. Order submission dynamics has been extensively studied for different markets, while order cancellation dynamics is less understood. There are two positions associated with a cancellation, that is, the price…
Resolves anomaly cancellation for M5-brane in M-theory.
In this paper, by combining modular forms and characteristic forms, we obtain general anomaly cancellation formulas of any dimension. For dimensional manifolds, our results include the gravitational anomaly cancellation formulas of Alvarez-Gaumé and Witten in dimensions 2, 6 and 10 (\cite{AW}) as special cases. …
We prove that a topological manifold (possibly with boundary) admitting a continuous cancellative binary operation is orientable. This implies that the Möbius band admits no cancellative continuous binary operation. This answers a question posed by the second author in 2010.