As part of Basel II's incremental risk charge (IRC) methodology, this paper summarizes our extensive investigations of constructing transition probability matrices (TPMs) for unsecuritized credit products in the trading book. The objective is to create monthly or quarterly TPMs with predefined sectors and ratings that …
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18 results for “TPMs”
Schwarz H surfaces can be continuously deformed into Meeks surfaces.
problem Classifying and understanding the relationship between Schwarz H surfaces and Meeks surfaces.
method Constructing a 2-parameter family of TPMS of genus three that contains both H and Meeks surfaces.
result Schwarz H surfaces can be continuously deformed into Meeks surfaces.
This study investigates porosity and topological properties of TPMS using machine learning.
problem Understanding the relationships between porosity and topological properties of TPMS.
method Application of machine learning techniques to analyze porosity and shape factor of TPMS.
result Conjectures suggesting polynomial relationships between porosity and shape factor of TPMS.
Transforming cylindrical packings into bicontinuous surfaces.
problem Understanding the early development of bicontinuous structures in plant plastids.
method Geometric modeling and computational simulations of cylinder packings.
result Specific cylinder packings with cubic symmetry transform into TPMS.
TPM improves medical image segmentation by separating foreground and background.
problem Few-shot medical image segmentation challenges due to background variability.
method Tied Prototype Model (TPM) focusing on foreground, adapting thresholds, and using class priors.
result TPM leads to improved segmentation accuracy compared to ADNet.
Study best arm identification in restless bandits with unknown TPMs.
problem Identify the best arm with fixed confidence in restless bandits with unknown TPMs.
method Proposed a policy for best arm identification and proved its expected stopping time matches the lower bound.
result The state-action visitation proportions match the optimal proportions under any asymptotically optimal policy.
Paper tackles anomaly detection in restless Markov arms with unknown TPMs.
problem Detecting an anomalous arm in a multi-armed bandit with unknown transition probability matrices.
method Developed a policy based on the principle of certainty equivalence, achieving the lower bound arbitrarily closely under specific assumptions.
result Achieved the lower bound on expected time required to find the odd arm index, demonstrating the policy's effectiveness.
Tractable models generate useful representations for unsupervised learning.
problem How to extract useful representations from black box models.
method Investigate Tractable Probabilistic Models (TPMs) for feature extraction.
result TPMs can generate embeddings by random query evaluations.
Minimal Twin Surfacesmath.DG
Minimal twin surfaces are found in material science, resembling crystal twins.
problem Finding mathematical and physical existence of twin surfaces.
method Employed Brakke's Surface Evolver to construct and analyze minimal twin surfaces.
result Strong evidence for the existence of D and G twins, and new cubic polyhedral models for G twins.
Improved regret bounds for combinatorial semi-bandits with probabilistically triggered arms.
problem Regret bounds containing an exponentially large factor of 1/p* in prior studies.
method Introducing a TPM bounded smoothness condition to remove the factor of 1/p*.
result Significantly better regret bounds for influence maximization and cascading bandits.
Improved MRI head anatomy segmentation using deep learning with multiple priors.
problem Challenges in segmenting head anatomy in MRI, especially with lesions.
method Added three types of prior information to a 3D convolutional network: spatial priors, morphological priors, and spatial context.
result Multiprior network improves segmentation performance, especially for abnormal anatomies.
New EM algorithm improves estimation of credit risk probabilities.
problem Estimating generator matrix for credit risk over shorter time frames.
method Expectation-Maximization (EM) algorithm for continuous time Markov chains.
result EM algorithm provides faster and more accurate estimates of probabilities of default.
New method for faster TPM from multivariate time series.
problem Mining predictive complex temporal patterns from multivariate time series.
method Fast Temporal Pattern Mining with Extended Vertical Lists.
result Significantly faster performance than previous algorithm.
Study best arm identification in restless Markov multi-armed bandits with state-dependent transitions.
problem Identify the best arm in a multi-armed bandit with time-varying states.
method Propose a sequential policy to select arms without knowing their exact TPMs.
result Upper and lower bounds on expected time to find the best arm match in a special case.
Study analyzes price change patterns across different market capitalizations using Markov chains.
problem Understanding price dynamics in limit order markets across various market capitalizations.
method Discrete-time Markov chain analysis of intraday price changes in NASDAQ100 tick data.
result Systematic patterns in price inertia and stability across market capitalizations are identified.
New algorithm for competing influence spread in unknown networks.
problem Maximizing influence spread in a social network with unknown probabilities.
method Combinatorial multi-armed bandit (CMAB) framework, Triggering Probability Modulated (TPM) condition, OCIM-TS, OCIM-OFU, OCIM-ETC.
result Sublinear Bayesian and frequentist regret for OCIM-TS and OCIM-OFU, respectively.
New algorithm for contextual combinatorial bandits with probabilistic arm triggering.
problem Optimizing decisions in dynamic environments with probabilistic arm availability.
method C^2-UCB-T and VAC^2-UCB algorithms with TPM and VM conditions.
result Achieved improved regret bounds for contextual combinatorial bandits.
The paper explores Cholesky decompositions for symmetric matrices and their geometric properties.
problem Understanding the structure and properties of symmetric matrices through Cholesky decompositions.
method Introducing cones of symmetric matrices, proving Cholesky-type factorizations, and showing geometric properties.
result Each symmetric matrix admits an uncountable family of Cholesky-type factorizations, and these cones are isometric Riemannian manifolds.