Research
On-device research index

arXiv research

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.

168,932 papers · 148 categories

Trend · papers per month

127253380506 · Jun 202019922001200920172026
48 results for conditional probability tables

The paper proposes a method to learn Bayesian networks with low rank conditional probability tables.

problem Learning the structure of Bayesian networks efficiently.
method Introduces low rankness for conditional probability tables, connects to Fourier transformation, and proposes a polynomial time algorithm.
result Correctly recovers the true directed structure of a low rank Bayesian network with few queries and polynomial samples.

A major problem for the learning of Bayesian networks (BNs) is the exponential number of parameters needed for conditional probability tables. Recent research reduces this complexity by modeling local structure in the probability tables. We examine the use of log-linear local models. While log-linear models in this con…

2013-01-23abs ↗pdf ↗

We study two-layer belief networks of binary random variables in which the conditional probabilities Pr[childlparents] depend monotonically on weighted sums of the parents. In large networks where exact probabilistic inference is intractable, we show how to compute upper and lower bounds on many probabilities of intere…

2013-01-30abs ↗pdf ↗

Two ML approaches compare in recognizing tables from historical records.

problem Recognizing rows and columns in hand-written registry books.
method Comparison of Conditional Random Field and Graph Convolutional Network.
result Both ML methods achieve an 89 F1 score for table detection.

Bounds derived for contract values in life insurance with financial market interaction.

problem Incompleteness in life tables for modern insurance products.
method Derivation of upper and lower bounds for hybrid functionals of lifetime under different assumptions.
result Characterization of worst- and best-case contract values over compatible mortality processes.

In a previous work, the first and third authors studied a random knot model for all two-bridge knots using billiard table diagrams. Here we present a closed formula for the distribution of the crossing numbers of such random knots. We also show that the probability of any given knot appearing in this model decays to ze…

2016-06-01abs ↗pdf ↗

In this article, I will present a paradox whose purpose is to draw your attention to an important topic in finance, concerning the non-independence of the financial returns (non-ergodic hypothesis). In this paradox, we have two people sitting at a table separated by a black sheet so that they cannot see each other and …

2019-03-05abs ↗pdf ↗

Compactness proven for isospectral Birkhoff billiard tables.

problem Proving compactness of isospectral Birkhoff billiard tables.
method Derived a hierarchical structure for integral invariants and used interpolating Hamiltonian.
result Compactness of equivalence classes of marked length isospectral Birkhoff billiard tables.

Proves a generalized table theorem for odd Euler characteristic surfaces.

problem Proving a generalized table theorem for surfaces with odd Euler characteristic.
method Using the square peg problem for smooth curves, the result is generalized to real valued functions on Riemannian surfaces with odd Euler characteristic.
result Proves the table conjecture for even functions on the two sphere.

Constrained sequence codes have been widely used in modern communication and data storage systems. Sequences encoded with constrained sequence codes satisfy constraints imposed by the physical channel, hence enabling efficient and reliable transmission of coded symbols. Traditional encoding and decoding of constrained …

2018-09-06abs ↗pdf ↗

This paper compiles and calculates triple point numbers for surface-links in Yoshikawa's table.

problem Determining the triple point number of surface-links in Yoshikawa's table.
method Using broken sheet diagrams, the paper compiles known triple point numbers and calculates or bounds the remaining ones.
result Compilation and calculation of triple point numbers for surface-links in Yoshikawa's table.

Many poker systems, whether created with heuristics or machine learning, rely on the probability of winning as a key input. However calculating the precise probability using combinatorics is an intractable problem, so instead we approximate it. Monte Carlo simulation is an effective technique that can be used to approx…

2018-08-22abs ↗pdf ↗

We use the Chebyshev knot diagram model of Koseleff and Pecker in order to introduce a random knot diagram model by assigning the crossings to be positive or negative uniformly at random. We give a formula for the probability of choosing a knot at random among all knots with bridge index at most 2. Restricted to this c…

2015-05-28abs ↗pdf ↗

Billiard trajectories and geodesics are closely related geometrically.

problem Understanding the relationship between billiard trajectories and geodesics on surfaces.
method Establishing mutual approximation results for billiard trajectories and geodesic segments on surfaces.
result For Riemannian billiard tables, there are families of fold-type surfaces such that every sequence of geodesic segments on these surfaces has a subsequence that converges to a billiard trajectory.

Deep RL controls anesthesia more accurately than traditional methods.

problem Controlling the level of unconsciousness during anesthesia.
method Deep Reinforcement Learning (DRL) to map patient state to propofol dosage.
result Deep RL model outperformed traditional controllers (1.7% vs 3.4% median absolute performance error).

Descriptive titles provide crucial context for interpreting tables that are extracted from web pages and are a key component of table-based web applications. Prior approaches have attempted to produce titles by selecting existing text snippets associated with the table. These approaches, however, are limited by their d…

2018-06-30abs ↗pdf ↗

In this paper we examine a novel addition to the known methods for learning Bayesian networks from data that improves the quality of the learned networks. Our approach explicitly represents and learns the local structure in the conditional probability tables (CPTs), that quantify these networks. This increases the spac…

2013-02-13abs ↗pdf ↗

Method combines clustering and matrix completion for missing data in I/O tables.

problem Reconstructing missing entries in World Input-Output (I/O) matrices due to data collection issues.
method Hierarchical clustering and Matrix Completion with LASSO-like nuclear norm penalty.
result The method effectively predicts missing values from previous and similar countries' data.

TableQnA answers web queries about lists and superlatives from HTML tables.

problem Answer web queries about lists and superlatives from HTML tables.
method Extract intent from queries, use structure-aware matching, and train models with automatic data generation.
result Significantly higher precision and coverage for list and superlative queries.

Proposes φφ-table for statistical SHAP explanations in regression models.

problem Lack of clear directional summaries, uncertainty, and fidelity in SHAP feature importance.
method SHAP importance selection, fitting a standardized linear surrogate, reporting coefficients, uncertainty, fidelity, and stability.
result Extends SHAP into a statistical global explanation with direction, uncertainty, fidelity, and stability.

Generative adversarial networks (GANs) implicitly learn the probability distribution of a dataset and can draw samples from the distribution. This paper presents, Tabular GAN (TGAN), a generative adversarial network which can generate tabular data like medical or educational records. Using the power of deep neural netw…

2018-11-27abs ↗pdf ↗

In this paper, we study the information-theoretic limits of learning the structure of Bayesian networks (BNs), on discrete as well as continuous random variables, from a finite number of samples. We show that the minimum number of samples required by any procedure to recover the correct structure grows as Ω(m)Ω(m) and $Ω…

2016-01-27abs ↗pdf ↗

Latent variable models are an elegant framework for capturing rich probabilistic dependencies in many applications. However, current approaches typically parametrize these models using conditional probability tables, and learning relies predominantly on local search heuristics such as Expectation Maximization. Using te…

2012-10-16abs ↗pdf ↗

Stable topological summary captures evolving dependency structure in dynamic Bayesian networks.

problem Missing larger-scale patterns in evolving dependency structures in dynamic Bayesian networks.
method Topological approach using Dynamic Bayesian Graphs and persistent homology.
result Stable topological summary (barcodes) captures evolving dependency structure in DBNs.

Open problem: Establishing bounds for Cayley-table completion to discover discrete algorithmic axioms.

problem Discovering discrete algorithmic axioms missing in deep learning.
method Cayley-table completion as a testbed for algorithmic complexity minimization.
result Formal exact recovery bounds for Cayley-table completion.

Study estimates and predicts dynamic traffic OD flows for improved DTA models.

problem Estimating and predicting time-varying OD trip tables for dynamic traffic assignment.
method Bi-level optimisation for OD flow estimation and time series prediction for OD demand.
result High capability of proposed OD demand estimation method to reduce DTA model error.