The maximal information coefficient (MIC) is a tool for finding the strongest pairwise relationships in a data set with many variables (Reshef et al., 2011). MIC is useful because it gives similar scores to equally noisy relationships of different types. This property, called {\em equitability}, is important for analyz…
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16 results for “MIC”
MIC consistently estimates dependence in large datasets.
problem Estimating dependence between variable pairs in large datasets.
method Proving consistency of MIC as an estimator.
result MIC is a consistent estimator of population statistic MIC*.
A measure of dependence is said to be equitable if it gives similar scores to equally noisy relationships of different types. Equitability is important in data exploration when the goal is to identify a relatively small set of strongest associations within a dataset as opposed to finding as many non-zero associations a…
Reshef & Reshef recently published a paper in which they present a method called the Maximal Information Coefficient (MIC) that can detect all forms of statistical dependence between pairs of variables as sample size goes to infinity. While this method has been praised by some, it has also been criticized for its lack …
ID3 generates near-optimal decision trees for DNFs under product distributions.
problem Understanding the optimality of decision trees generated by ID3.
method Introducing a new metric (MIC) to measure the optimality of ID3-generated trees and comparing it with other algorithms.
result The TopDown variant of ID3 is near-optimal in learning read-once DNFs under product distributions, while another variant is not.
Given a high-dimensional data set we often wish to find the strongest relationships within it. A common strategy is to evaluate a measure of dependence on every variable pair and retain the highest-scoring pairs for follow-up. This strategy works well if the statistic used is equitable [Reshef et al. 2015a], i.e., if, …
Reshef et al. recently proposed a new statistical measure, the "maximal information coefficient" (MIC), for quantifying arbitrary dependencies between pairs of stochastic quantities. MIC is based on mutual information, a fundamental quantity in information theory that is widely understood to serve this need. MIC, howev…
MIC improves VAR order selection accuracy.
problem Order selection in VAR models for accurate forecasting.
method MIC based on expected squared error loss.
result MIC consistently estimates true VAR order.
Study mutual insurance market dynamics using mean field games.
problem Understanding strategic interactions and wealth distribution in mutual insurance companies.
method Extended mean field game framework, mean field forward-backward stochastic differential equations (MF-FBSDE), deep BSDE algorithm.
result Established global-in-time existence and uniqueness of Nash equilibrium strategy.
Modeling social network activity through user and topic interaction.
problem Understanding complex dynamics of opinion formation in social networks.
method Mixture of Interacting Cascades (MIC) model of marked multidimensional Hawkes processes.
result MIC achieves superior performance in modeling information cascade spread.
The paper proposes a framework to adjust dependency measure estimates for chance.
problem Challenges in interpreting and ranking dependency measures on finite samples.
method Simple adjustments to improve interpretability and accuracy of dependency measures.
result Improves interpretability and accuracy of dependency measures, demonstrated on MIC and random forests.
Paper uses algebraic signatures to identify probabilistic structures in empirical data.
problem Identifying probabilistic structure from observed binomials in empirical probability tensors.
method Treating vanishing binomials as algebraic signatures, matching signatures to identify models without parameter estimation.
result The method successfully identified rank-one structures in real language data, revealing interpretable sets of words.
Study geodesics on nested non-holonomic systems.
problem Interplay between geodesics on related non-holonomic systems.
method Hamiltonian formalism and geometric preliminaries.
result Presented several geometric examples, including exotic spheres and twistor space.
Authors use exotic 4-manifolds to model quantum computing and measurements.
problem Modeling quantum computing and measurements using exotic space-time structures.
method Choose the fundamental group of an exotic 4-manifold to encode quantum states and measurements.
result Exotic models encode a variety of standard contextual geometries in quantum measurements.
Research on the correlation between text emotion mining and stock market based on deep learningq-fin.ST
This study uses deep learning to analyze stock market sentiment from financial forums.
problem Improving stock market prediction accuracy through emotional analysis.
method Crawling financial forum data, training Bert model on financial corpus, using MIC for comparison.
result BERT model's emotional analysis of financial texts correlates with stock market fluctuations.
Extends PoS proof-of-stake transaction fee mechanism with miner utility model.
problem Designing a transaction fee mechanism for PoS protocol that incorporates miner utility.
method Introduced a new mechanism (BSP(θ)) incorporating a parameter θ to ensure user and miner incentives.
result The new mechanism (BSP(θ)) satisfies user and miner incentives and contract proofness.