Machine learning aids in bridging international news gaps.
problem Limited global understanding due to segmented news and language barriers.
method Combining machine learning, journalism studies, and statistics.
result Improved global perspective on international issues.
Optimized execution model using interbank and internal liquidity.
problem Minimizing market impact in trading.
method Integrates interbank limit and market orders with internal market-making liquidity.
result Reduces market impact and improves execution efficiency.
This paper reviews and proposes a new approach for evaluating internal cluster validation indices.
problem Selecting the best-performing unsupervised classification algorithm without external information.
method Examines and proposes a new evaluation approach for internal validation indices.
result Suggests a new evaluation approach for internal validation indices.
This paper develops a non-Bayesian methodology to analyze the time-varying structure of international linkages and market efficiency in G7 countries. We consider a non-Bayesian time-varying vector autoregressive (TV-VAR) model, and apply it to estimate the joint degree of market efficiency in the sense of Fama (1970, 1…
Study uses Google matrix analysis to show how COVID-19 changed international trade flows.
problem Impact of COVID-19 on international trade patterns.
method Google matrix analysis of World Trade Network (WTN), including PageRank, CheiRank, and reduced Google matrix.
result Significant changes in international trade flows due to the pandemic, affecting export and import balances.
New findings show that some knotted surfaces remain distinct even after many stabilizations.
problem Understanding the behavior of knotted surfaces after internal stabilizations.
method Analyzing the properties of smoothly knotted surfaces and their behavior under internal stabilizations.
result There is no upper bound on the number of internal stabilizations required for some knotted surfaces to remain distinct.
A new clustering evaluation index based on density estimation.
problem Improving internal clustering evaluation indices.
method The index is a mixture of Ambiguous and Similarity sub-indices, calculated using density estimation.
result The new index significantly outperforms other internal clustering evaluation indices.
Model reconstructs and simulates international trade networks under policy changes.
problem Reconstructing and simulating international trade networks under policy changes.
method Maximizing entropy based on local trade information to reconstruct networks; simulating structural changes using trade tariffs.
result Trade networks can be successfully reconstructed and simulated under policy changes.
We present a comprehensive classification of supersymmetric vacua of M-theory compactification on seven-dimensional manifolds with general four-form fluxes. We analyze the cases where the resulting four-dimensional vacua have N = 1,2,3,4 supersymmetry and the internal space allows for SU(2), SU(3) or G_2 structures. In…
New method learns internal model from expert demonstrations to estimate rewards.
problem Lack of complete or good action information from expert demonstrations.
method Agent learns internal model of observations from expert state trajectories to estimate rewards.
result Successfully trains good policies from expert game-play videos.
Internal Lagrangians derived from variational principles.
problem Reproducing the principle of stationary action in variational geometry.
method Introducing stationary points of internal Lagrangians, establishing connections with symmetries and conservation laws, and investigating relations between non-degenerate and internal Lagrangians.
result Noether's theorem reformulated in terms of internal Lagrangians.
Model predicts internal fraud in retail banking is cyclical and influenced by corruption.
problem Predicting and mitigating internal fraud losses in retail banking.
method Developed a dynamic model considering internal factors and macroeconomic indicators.
result Internal fraud losses are pro-cyclical and positively affected by corruption perceptions.
Paper optimizes international portfolios with new copula-based scenario generation.
problem Optimizing international portfolios with realistic uncertainty models.
method Two-stage stochastic model, regular-vine copula for scenario generation, including transaction costs.
result Proposed method yields better risk-return portfolios than standard approaches.
For many externally driven complex systems neither the noisy driving force, nor the internal dynamics are a priori known. Here we focus on systems for which the time dependent activity of a large number of components can be monitored, allowing us to separate each signal into a component attributed to the external drivi…
A new CVI called DSI evaluates clustering results without true labels.
problem No universal CVI for clustering without true labels.
method DSI based on data separability measure.
result DSI is an effective, unique, and competitive CVI.
Examines international taxation's impact on Georgian businesses.
problem Impact of international taxation on Georgian business entities.
method Analyzes types, features, and approaches of international taxation.
result Provides recommendations to correct current taxation issues.
Study benchmarks 26 clustering validity measures.
problem Determining the best clustering solution from candidates.
method Enhanced revision of previous methodology with three sub-methodologies.
result Comprehensive evaluation of 26 internal validity indexes.
New risk measures use internal resources to make positions acceptable.
problem Monetary risk measures can lead to infinite values and lack flexibility.
method Intrinsic risk measures use internal resources and a free choice of eligible assets.
result Intrinsic risk measures avoid infinite values and preserve key properties.
This study assesses how economic shocks affect the efficiency and robustness of international pesticide trade networks.
problem Economic shocks impact the efficiency and robustness of international pesticide trade networks.
method Simulations were used to quantify efficiency and robustness under different economic shocks. Three strategies were tested: descending, random, and ascending node removal.
result The international pesticide trade networks became more efficient and robust except for clustering coefficient. Import-oriented economies were more vulnerable to shocks.
Internal node bagging uses dropout-like training to improve model fitting with fewer parameters.
problem Improving model fitting with fewer parameters.
method Explicitly forces a group of nodes to learn a certain feature, combining them in inference time.
result Internal node bagging performs significantly better than dropout on small models.
This paper proposes using DLT to expand SDRs for global stability.
problem Political instability and currency wars threaten global value chains.
method Proposes a two-step approach for IMF to integrate DLT into SDRs.
result SDRs can be redefined as a new reserve currency in a decentralized world.
Study finds internal view preferred over external view in defining startups.
problem Insufficient understanding of how to start a new business.
method Empirical study with 701 entrepreneurs reflecting on nine resource categories and three business mission elements.
result Tendency to favor internal view over external view, stronger in stable economies.
New method infers intent from suboptimal behavior by modeling incorrect internal beliefs about dynamics.
problem Inferring intent from suboptimal human behavior using traditional methods assumes near-optimality, which is not always valid.
method Model suboptimal behavior as internal model misspecification, estimating incorrect beliefs about dynamics.
result Accurately models human intent by accounting for internal model inaccuracies.
There are few papers about the international trade of flowers, so it is believed that this paper, with this topic, could be an important contribution to the international scientific community. It is intended to analyze if the international trade flowers tendencies and policies are adapted to the actual world global con…
Spain uses DEA to select international markets for exports.
problem Choosing the best international markets for Spanish exports.
method Output-oriented DEA model considering multiple validated inputs and outputs.
result Identifies efficient regions generating higher benefits with lower costs.
Improved speech recognition model with better performance.
problem Speech recognition accuracy on Librispeech.
method Integrates an external language model with an internal LM correction.
result Over 14% relative improvement in performance.
A new method generates natural-looking adversarial examples by bounding internal activation values.
problem Creating natural-looking adversarial examples that closely mimic the original input.
method Bounding internal activation values through a distribution quantile bound and polynomial barrier loss function.
result Our attack achieves similar success and confidence levels as state-of-the-art methods but with more natural-looking perturbations.
New internal symmetry found for Lie pair algebra.
problem Understanding Lie pair structures and their associated algebras.
method Introduced a Lie algebra action by Der(L) on the L_{≤3} algebra.
result Found internal symmetry of the L_{≤3} algebra.
To quantify an operational risk capital charge under Basel II, many banks adopt a Loss Distribution Approach. Under this approach, quantification of the frequency and severity distributions of operational risk involves the bank's internal data, expert opinions and relevant external data. In this paper we suggest a new …
Introduces internal Lagrangians for differential equations and connects them to presymplectic structures.
problem Understanding the geometry of differential equations and their solutions.
method Develops a spectral sequence related to internal Lagrangians and investigates connections to presymplectic structures.
result Interprets a term in Vinogradov's spectral sequence for gauge theories.
The UN General Debate Corpus analyzes speeches from UN member states to reveal their political positions.
problem Lack of data on state preferences in international politics.
method Text analysis of over 7,700 speeches from 1970-2016.
result Demonstrates how the UN General Debate Corpus can reveal country positions on various policy dimensions.
New moving average adapts weight dynamically based on polynomial and wavefunction.
problem Lagging traditional moving averages in adjusting to changes in data.
method Develops a moving average with weight as a polynomial of a wavefunction from an eigenproblem.
result Immediate 'switch' without lag, adapting to changes in data.
Study improves stock price prediction by integrating international markets using deep learning.
problem Complex cross-correlation between international stock markets.
method Multimodal deep learning to forecast stock prices.
result Early and intermediate fusion models outperform late fusion and single modality models.
Proposes a framework to predict stock movements by integrating multi-order and internal dynamics.
problem Predicting stock movements with multi-order and internal dynamics.
method Temporal generative filters and hypergraph attentions using wavelet basis.
result Framework outperforms state-of-the-art methods in terms of profit and stability.
A conceptor-based approach helps robots recognize human internal states.
problem Recognizing human internal states for diagnostic purposes in autism therapy.
method A conceptor-based classifier to classify internal states.
result Initial results show potential for detailed diagnostic information.
Study examines flaws in probing LLMs' knowledge and introduces a new method.
problem Flaws in existing methods for probing the veracity of LLMs' internal knowledge.
method sAwMIL (Sparse-Aware Multiple-Instance Learning) combining multiple-instance learning with conformal prediction.
result LLMs encode a third type of signal distinct from true and false.
Investigates optimal strategies for market makers using internal liquidity.
problem Optimizing strategies for market makers with internal liquidity.
method Investigates optimal multi-objective strategy for market makers with internal liquidity.
result Draws important qualitative insights for real-world trading.
Neural networks learn distance-based representations, not just intensity.
problem Understanding how neural networks interpret and learn from internal activations.
method Manipulated ReLU and Absolute Value activations to observe sensitivity to distance and intensity perturbations.
result Neural networks are highly sensitive to small distance-based perturbations, challenging the intensity-based interpretation.
New flows on convex real projective structures on surfaces.
problem Deforming convex real projective structures on surfaces.
method Introducing internal bulging and eruption flows on the deformation space C(S).
result Eruption flows and generalized twist flows give a half-dimensional family of commuting flows.
New method detects long-term structures with internal dynamics in time series data.
problem Identifying patterns across time in data growth.
method Adaptive identification of majority overlaps between groups at different time points.
result Detection of persistent structural elements with internal dynamics.
Mathematical model predicts international trade and global economy dynamics.
problem Understanding complex international trade and economy interactions.
method Developed a mathematical model for non-equilibrium processes in open systems.
result Predicted model accurately reflects international trade and economy.
Random feature maps improve forecasting with cheaper computation.
problem Improving forecasting accuracy with random feature maps.
method Developed a hit-and-run algorithm to select optimal internal weights.
result Optimal internal weights lead to superior forecasting skill.
Reconstructing a manifold from internal scattering data.
problem Reconstructing a compact Riemannian manifold from internal scattering data.
method Generic assumption of the metric allows reconstruction from boundary measurements of geodesic exit directions.
result Isometric reconstruction of the manifold from boundary scattering data.
Unified model explains international trade patterns using reinforced urns.
problem Understanding the complex patterns of international trade networks.
method A unified modelling framework using reinforced urns and the Reinforced Urn Process.
result The model predicts power law behavior and accounts for various network properties.
Study uses AI to predict changes in international public finances based on US markets.
problem Understanding correlations between US and international public finances.
method Artificial intelligence and neural networks to model and predict changes.
result Neural network model achieved MSE of 2.79, indicating significant correlation and impact of US market volatility on international markets.
LLMs struggle with zero-shot annotation tasks due to model-internalized priors.
problem Impact of model-internalized priors on LLM performance in zero-shot annotation tasks.
method Investigated three dimensions: familiarity, decision stickiness, and susceptibility to misaligned task definitions.
result Nearly two-thirds of zero-shot errors are resistant to correction, with a rescue rate of 34.8%. Definition-Specific Familiarity (DSF) shows a positive association with model performance.
Brazil proposes a new BRICS trade currency to dominate international trade.
problem Dominance of BRICS currency in international trade.
method Mathematical model of influence battle between three currencies, using trade flows and weights in global trade.
result By 2012, about 58% of countries preferred trading with the BRICS currency.
Method infers internal model from rational foraging behavior.
problem Discover how the brain represents and computes dynamic beliefs.
method POMDP model, EM algorithm, maximum likelihood estimation.
result Successfully recovered internal model and reward function of foraging agents.