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.
Novel approach to estimate P300 BCI efficiency using SNR.
A transformer model improves spell correction with hierarchical attention.
Real-time spell checker adapts to new languages.
This study analyses the duration dependence of events that trigger volatility persistence in stock markets. Such events, in our context, are monthly spells of contiguous price decline or negative returns for the S&P500 stock market index over the last 145 years. Factors known to affect the duration of these spells are …
Chatbot uses BERT to handle financial investment questions, improving accuracy and decision-making.
We further study the incidence relations that arise from the various subtowers, known as Baby Monster, which exist within the -Monster Tower. This allows us to complete the class spelling rules. We also present a method of calculating the various Baby Monster that appear within the Monster Tower.
Synthetic noise training improves machine translation robustness to spelling mistakes.
A new transformer model corrects diacritics and typos in multiple languages.
In many recent applications, data is plentiful. By now, we have a rather clear understanding of how more data can be used to improve the accuracy of learning algorithms. Recently, there has been a growing interest in understanding how more data can be leveraged to reduce the required training runtime. In this paper, we…
We present Listen, Attend and Spell (LAS), a neural network that learns to transcribe speech utterances to characters. Unlike traditional DNN-HMM models, this model learns all the components of a speech recognizer jointly. Our system has two components: a listener and a speller. The listener is a pyramidal recurrent ne…
Winterization of Texas power system profitable but risky, estimated at $11.74bn over 30 years.
Improves diversity of text-to-image models without sacrificing FID.
The Monster tower, also known as the Semple tower, is a sequence of manifolds with distributions of interest to both differential and algebraic geometers. Each manifold is a projective bundle over the previous. Moreover, each level is a fiber compactified jet bundle equipped with an action of finite jets of the diffeom…
In automatic speech recognition (ASR) what a user says depends on the particular context she is in. Typically, this context is represented as a set of word n-grams. In this work, we present a novel, all-neural, end-to-end (E2E) ASR sys- tem that utilizes such context. Our approach, which we re- fer to as Contextual Lis…
Grapheme ASR improves with G2G model that corrects spelling errors.
We review (non-abelian) extensions of a given Lie algebra, identify a 3-dimensional cohomological obstruction to the existence of extensions. A striking analogy to the setting of covariant exterior derivatives, curvature, and the Bianchi identity in differential geometry is spelled out. In the new version references ad…
Neural network optimizes learning sequence for reading words.
System solves author name ambiguity in e-commerce catalogs.
Attention-based encoder-decoder architectures such as Listen, Attend, and Spell (LAS), subsume the acoustic, pronunciation and language model components of a traditional automatic speech recognition (ASR) system into a single neural network. In previous work, we have shown that such architectures are comparable to stat…
The universal perturbative invariants of rational homology spheres can be extracted from the Chern-Simons partition function by combining perturbative and nonperturbative results. We spell out the general procedure to compute these invariants, and we work out in detail the case of Seifert spaces. By extending some prev…
Direct acoustics-to-word (A2W) models in the end-to-end paradigm have received increasing attention compared to conventional sub-word based automatic speech recognition models using phones, characters, or context-dependent hidden Markov model states. This is because A2W models recognize words from speech without any de…
Study modular class of Lie ∞-algebroids and their adjoint actions.
Objective: Using traditional approaches, a Brain-Computer Interface (BCI) requires the collection of calibration data for new subjects prior to online use. Calibration time can be reduced or eliminated e.g.~by transfer of a pre-trained classifier or unsupervised adaptive classification methods which learn from scratch …
Framework detects changes in causal dependence between variables.
The paper defines and studies the category of Z-graded manifolds, including their intrinsic structure and formal properties.
End-to-end model detects articulatory features from speech data.
Having a sequence-to-sequence model which can operate in an online fashion is important for streaming applications such as Voice Search. Neural transducer is a streaming sequence-to-sequence model, but has shown a significant degradation in performance compared to non-streaming models such as Listen, Attend and Spell (…
Paper trains models to resist string transformations.
AV-ASR system improves speech recognition with visual context.
We propose SEARNN, a novel training algorithm for recurrent neural networks (RNNs) inspired by the "learning to search" (L2S) approach to structured prediction. RNNs have been widely successful in structured prediction applications such as machine translation or parsing, and are commonly trained using maximum likelihoo…
We map the recently proposed notions of algorithmic fairness to economic models of Equality of opportunity (EOP)---an extensively studied ideal of fairness in political philosophy. We formally show that through our conceptual mapping, many existing definition of algorithmic fairness, such as predictive value parity and…
The abstract explains how word and relation representations capture semantic meaning.
Diffusion models can memorize training data, limiting their creativity and privacy.
In the probabilistic topic models, the quantity of interest---a low-rank matrix consisting of topic vectors---is hidden in the text corpus matrix, masked by noise, and the Singular Value Decomposition (SVD) is a potentially useful tool for learning such a low-rank matrix. However, the connection between this low-rank m…
There are two themes in the present paper. The first one is spelled out in the title, and is inspired by an attempt to find an analogue of Hersch-Yang-Yau estimate for of surfaces in symplectic category. In particular we prove that every split symplectic manifold admits a compatible Riemannian …
Model shows how banks' fears of future defaults can cause immediate financial stress.
We develop a Chern character map for twisted equivariant non-abelian cohomology.
Paper analyzes convergence of ODE samplers in Wasserstein distances.
This paper is motivated by questions about averages of stochastic processes which originate in mathematical finance, originally in connection with valuing the so-called Asian options. Starting with research of Yor's in 1992, these questions about exponential functionals of Brownian motion have been studied in terms of …
Automated generation of medical reports from chest x-rays using expert annotations.
SpecAugment improves speech recognition with simple feature augmentation.
Deep learning model extracts location references from tweets during emergencies.
Automated decision making is used routinely throughout our everyday life. Recommender systems decide which jobs, movies, or other user profiles might be interesting to us. Spell checkers help us to make good use of language. Fraud detection systems decide if a credit card transactions should be verified more closely. M…
Seq2seq ASR adapts to speakers, improving performance by 25%.
The generalization of Frobenius' theorem to foliations with singularities is usually attributed to Stefan and Sussmann, for their simultaneous discovery around 1973. However, their result is often referred to without caring much on the precise statement, as some sort of magic spell. This may be explained by the fact th…
BCI system improves word selection efficiency using sequential best-arm identification.
TeLeS improves ASR confidence estimation by considering temporal alignment and lexical errors.
Survival analysis models predict loan write-off risk under IFRS 9.