East African tech experts identify machine learning challenges.
problem Machine learning research needs in East African tech industry.
method 46 interviews with tech professionals.
result Concrete machine learning problems identified.
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48 results for “East African tech”
What are East Africa's industrial opportunities? In this article we explore this question by using the Product Space to study the productive structure of five south-east African countries: Kenya, Mozambique, Rwanda, Tanzania and Zambia. The Product Space is a network connecting products that tend to be exported by the …
A statistical analysis of financial, economic, and demographic indicators performed by the authors demonstrates (1) that the main countries of East Africa (Uganda, Kenya, and Tanzania) have not escaped the Malthusian Trap yet; (2) that this countries are not likely to follow the "North African path" and to achieve this…
Trains neural machine translation models for 5 Southern African languages.
problem Lack of shared resources and reproducible results for African languages.
method Trained neural machine translation models on publicly-available datasets.
result Provides code for training and evaluating models, aiming to spur future research.
Neural machine translation models trained for 5 South African languages.
problem Lack of resources and research for machine translation in African languages.
method Training neural machine translation models for 5 South African languages using modern techniques.
result Promises of neural machine translation for African languages.
This paper is a contribution to interweaving two lines of research that have progressed in separate ways: network analyses of international trade and the literature on African trade and development. Gathering empirical data on African countries has important limitations and so does the space occupied by African countri…
Paper aims to improve education online in South Africa using NMT for Setswana.
problem Inclusion of machine translation for low-resourced local languages in online education.
method Demonstrates state-of-the-art performance on English-to-Setswana translation using the Transformer architecture.
result Current NMT techniques show promise for African languages, beating previous methods by 5.33 BLEU points.
SAGDA generates synthetic agricultural datasets to improve ML in African farming.
problem Data scarcity in African agriculture limits machine learning innovations.
method SAGDA is an open-source Python toolkit that generates, augments, and validates synthetic agricultural datasets.
result SAGDA enhances ML applications in agriculture, such as yield prediction and fertilizer recommendation.
COMPAS recidivism predictions show racial bias against African Americans, study finds.
problem Racial bias in recidivism prediction algorithms.
method Causal analysis using FACT, a fairness measure grounded in causal inference.
result COMPAS shows racial bias against African American defendants, robust to unmeasured confounding.
Develops a deep learning framework to predict future tech directions for high-tech companies.
problem Difficult task in predicting future R&D trends for high-tech companies due to complexity and variety of factors.
method Deep Technology Forecasting (DTF) framework with three components: PCR, CTR, and DTT neural network.
result DTF framework precisely predicts future tech emphasis of companies using hybrid factors.
EAST compresses deep ConvNets for tiny memory nodes.
problem Memory constraints in tiny devices for deep ConvNets.
method Encoding-Aware Sparse Training (EAST) with adaptive group pruning and LZ4 weight encoding.
result EAST achieves deep memory compression with lower sparsity and higher accuracy.
Study examines tech stocks' reactions to Facebook data leak scandal.
problem Impact of Facebook data leak scandal on U.S. tech stocks.
method Clustering method to identify related companies, CAR to measure impact.
result Overall tech sector showed no adverse impact, but Facebook's performance was negatively affected.
A framework for simulating systemic risk and its application to the South African banking sectorq-fin.RM
Framework simulates systemic risk in South African banking sector.
problem Monitoring systemic risk in banking systems.
method Network-based approach considering shock propagation and systemic market risks.
result Simulated systemic risk spikes align with subjective assessments.
Study compares market microstructure between two South African exchanges.
problem Understanding price response dynamics and market microstructure differences between two South African exchanges.
method Comparative analysis of returns distributions, auto-correlations, price impact, and trading costs on different time scales.
result Similar stylized facts emerge as measurement time scale increases, but price responses vary significantly.
Model uses HS-FP framework for South African asset allocation.
problem Develops a flexible non-parametric asset allocation model for South African markets.
method Historical Simulation with Flexible Probabilities (HS-FP) framework, using relative entropy for distribution estimation.
result HS-FP model outperforms classic MVO and EW benchmarks in out-of-sample performance.
Machine learning predicts seasonal precipitation for East Africa.
problem Predicting seasonal precipitation for East Africa using machine learning.
method Dimension reduction via EOFs, large-scale climate variability indices as features, interpretable ML algorithm.
result The ML approach shows significant positive skill in predicting precipitation for OND season, comparable to ECMWF forecasts.
In this paper, we analyse the South African implied volatility in various setting. We assess the information content in SAVI implied volatility using daily markets data. Our empirical application is focused on the FTSE/JSE Top 40 index and we emphasize our models performance in distinct sub-periods. Our results are com…
The Tech Decouplingq-fin.ST
Tech sector decouples from non-tech sectors post-2015, predicting economic growth.
problem Understanding the relationship between technology and economic growth.
method ARIMA modeling, stationarity tests, data wrangling, exploratory data analysis.
result The technology sector decouples from non-technology sectors post-2015 and predicts economic growth.
New model forecasts power consumption with high accuracy over months to years.
problem Probabilistic forecasting of power consumption in a middle-term horizon.
method Combines traditional time-series analysis with weather conditions using Gaussian Process.
result Promising results in Out-of-Sample density forecasts up to one year.
EAST aligns neural network classifiers with user-defined evaluation metrics.
problem Mismatch between neural network training and evaluation metrics leads to suboptimal performance.
method EAST uses dynamic thresholding, soft-set confusion matrix, and annealing to align neural network predictions with target evaluation metrics.
result EAST improves alignment between training objectives and evaluation metrics, outperforming existing methods.
The paper uses deep learning to detect asset price bubbles in tech stocks.
problem Detecting financial asset price bubbles using deep learning.
method Deep learning techniques applied to call option prices for financial asset bubbles detection.
result The proposed deep learning algorithm provides a theoretical foundation for positive and continuous stochastic asset price processes.
Deep learning applied to coastal LULC classification post-earthquake.
problem Automatic land cover classification on coastal areas post-disaster.
method Manual tracing, simple image segmentation, image transformation using deep learning.
result Deep learning method showed over 69% accuracy for vegetation classification.
Study analyzes climate-tech investments across 14 sectors.
problem Accelerating climate-tech innovation in nascent value chains.
method Analysis of 4,172 firms and 12,929 investments over 15 years.
result Only 15% of firms develop end products, 59% support them, and 26% develop services.
Market Efficiency in Foreign Exchange Marketsphysics.soc-ph
We investigate the relative market efficiency in financial market data, using the approximate entropy(ApEn) method for a quantification of randomness in time series. We used the global foreign exchange market indices for 17 countries during two periods from 1984 to 1998 and from 1999 to 2004 in order to study the effic…
This paper evaluates investment risks in LATAM AI startups using DCF method.
problem Unique challenges and risks faced by LATAM tech startups.
method Total Addressable Market (TAM), Serviceable Available Market (SAM), and Serviceable Obtainable Market (SOM) metrics; Discounted Cash Flow (DCF) method.
result Developed a ranking of emerging powers in Latin America for tech startup investment.
Paper presents mdfa to identify victims of discrimination in black box classifiers.
problem Identifying victims of discrimination in black box classifiers.
method Reduces discrimination measurement to matching distributions and sensitive attribute coincidence prediction.
result Identifies African-American individuals at high risk of violent recidivism.
hood2vec identifies urban area similarity via mobility networks.
problem Identifying similar urban areas using mobility networks.
method Learning node embeddings of the mobility network from Foursquare check-ins.
result Mobility dynamics capture different aspects of urban area similarity than venue types.
In this study, the authors develop a structural model that combines a macro diffusion model with a micro choice model to control for the effect of social influence on the mobile app choices of customers over app stores. Social influence refers to the density of adopters within the proximity of other customers. Using a …
Study compares sentiment spillover networks from news and social media in tech companies.
problem Understanding how sentiment information flows between companies through news and social media.
method Network-based transfer entropy method to measure and compare sentiment spillover.
result News shows stronger information flow among tech companies after COVID-19.
New algorithm for quickly deciding on tech innovations to maximize ROI.
problem Maximizing ROI in repeated decision-making for tech innovations.
method Developed a novel algorithm for learning optimal decision-making policies over innovation proposals.
result Algorithm converges to optimal policy with a rate of order .
Correlation Networks Among Currenciesphysics.soc-ph
By analyzing the foreign exchange market data of various currencies, we derive a hierarchical taxonomy of currencies constructing minimal-spanning trees. Clustered structure of the currencies and the key currency in each cluster are found. The clusters match nicely with the geographical regions of corresponding countri…
ChatGPT predicts stock trends from Twitter sentiment, showing positive effects.
problem Predicting stock market trends using social media sentiment.
method Used ChatGPT for sentiment analysis of Twitter posts about Microsoft and Google.
result ChatGPT's predictions correlated positively with stock performance.
This is a write-up of the author's talk in the conference "Algebraic Geometry in East Asia 2016" held at the University of Tokyo in January 2016. We give a survey on a series of papers of the author and his collaborators Daniel Pomerleano and Kazushi Ueda where we show how Strominger-Yau-Zaslow (SYZ) transforms can be …
Proposes a new method for determining LGD discount rates based on cost of capital.
problem Determining an appropriate discount rate for LGD estimation.
method Market-consistent pricing of defaulted loan portfolios to infer discount rates.
result Discount rates reflect both undiversifiable risk and time value of money.
A Deep Zero-Inflated Model for Detecting North Atlantic Right Whale Presence
problem Balancing marine conservation and blue economy management
method Deep Zero-Inflated Bernoulli model
result Improved model adequacy and predictive performance
These notes were prepared to supplement the talk that I gave on Feb 19, 2004, at the First East Asian School of Knots and Related Topics, Seoul, South Korea. In this article I review aspects of the interconnections between braids, knots and contact structures on Euclidean 3-space. I discuss my recent work with William …
We redefine SICR-events for better loan classification under IFRS 9.
problem Ambiguity in SICR-event definition under IFRS 9.
method Proposed alternative framework with three parameters: delinquency, stickiness, and outcome period. Varying these parameters, we generated 27 unique SICR-definitions and fitted logistic regression models.
result The proposed SICR-models outperform the PD-comparison approach as an early-warning system for credit losses.
Tool uses text mining to define innovative tech fields from abstracts.
problem Defining scope in dynamic, multidisciplinary tech projects.
method Text mining of Elsevier's Scopus abstracts.
result Tool provides crucial information for tech field definition.
Frolicher spaces and smooth mappings form a cartesian closed category. It was shown in our previous paper [Far East Journal of Mathematical Sciences, 35 (2009), 211-233] that its full subcategory of Weil exponentiable Frolicher spaces is cartesian closed. By emancipating microlinearity from within a well-adapted model …
We construct a statistical indicator for the detection of short-term asset price bubbles based on the information content of bid and ask market quotes for plain vanilla put and call options. Our construction makes use of the martingale theory of asset price bubbles and the fact that such scenarios where the price for a…
Mirzakhani extended curve counting from simple to all curves.
problem Counting curves in the mapping class group orbit with length at most L.
method Low-tech argument showing general result from simple curves.
result Derived the asymptotic growth of curves for arbitrary curves.
A case study of speculative financial bubbles in the South African stock market 2003-2006physics.soc-ph
We tested 45 indices and common stocks traded in the South African stock market for the possible existence of a bubble over the period from Jan. 2003 to May 2006. A bubble is defined by a faster-than-exponential acceleration with significant log-periodic oscillations. The faster-than-exponential acceleration characteri…
DeepEthnic classifies faces into ethnic groups with high accuracy.
problem Classifying faces into ethnic groups using machine learning.
method Transfer learning from a large-scale data recognition network.
result State-of-the-art success rates for four ethnic groups.
Obtaining detailed and reliable data about local economic livelihoods in developing countries is expensive, and data are consequently scarce. Previous work has shown that it is possible to measure local-level economic livelihoods using high-resolution satellite imagery. However, such imagery is relatively expensive to …
In this paper, we propose a new deep feature selection method based on deep architecture. Our method uses stacked auto-encoders for feature representation in higher-level abstraction. We developed and applied a novel feature learning approach to a specific precision medicine problem, which focuses on assessing and prio…
Dual risk models are popular for modeling a venture capital or high tech company, for which the running cost is deterministic and the profits arrive stochastically over time. Most of the existing literature on dual risk models concentrated on the optimal dividend strategies. In this paper, we propose to study the optim…
Study uses web search data to analyze tech startups growth.
problem Analyzing growth dynamics of tech startups.
method Utilized Google Trends data for 241 US-based tech startups.
result Web search traffic correlates positively with tech startup growth.
Geoeconomic analysis of venture capital portfolios reveals key emerging tech domains and countries.
problem Quantifying geoeconomic power and technological sovereignty through venture capital data.
method Economic complexity methods applied to venture capital portfolios and RVA metrics.
result Cloud Computing, Cybersecurity Tools, and Medtech have the highest concentration of specialization among high-GCI countries.