| 1 |
A. Nygård |
Agent-System Interface Designs for Enterprise Platforms: A Comparative Empirical Study |
June 2026 |
Ardoq |
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| 2 |
A. von Hertzen |
Interpretability-Driven Regularization for Station-Level Weather Forecasting |
May 2026 |
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video |
| 3 |
I. Viita |
Structuring Legacy Data: Classification Pipeline for Construction Industry Archives |
May 2026 |
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video |
| 4 |
B. Zheng |
Exploring the structure in deep networks: Group, manifold and category theory |
Dec. 2025 |
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| 5 |
V. Niemi |
Diagnosing and improving a maintenance contract churn prediction model |
Dec. 2025 |
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video |
| 6 |
A. Hämäläinen |
Improving retrieval-augmented generation with LLM-as-a-judge evaluation |
Nov. 2025 |
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| 7 |
S. Monira |
FedSock & FedBlue: Scalable decentralized federated learning systems with generalized total variation minimization |
Nov. 2025 |
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| 8 |
A. Pavlyuk |
Federated learning with multi-layer perceptron for sensor drift compensation in direct-ethanol fuel cells |
July 2025 |
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video |
| 9 |
S. Rachidi |
Explainable machine learning in cancer survival prediction — A case study of myeloma patients |
July 2025 |
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| 10 |
C. Fait |
Designing a data pipeline for total column greenhouse gas measurements with portable EM27/SUN spectrometers |
July 2025 |
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| 11 |
L. Tuominen |
Robust tap gesture recognition on wearable devices with domain adaptation |
July 2025 |
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| 12 |
O. Lauronen |
Unsupervised semantic matching of support tickets |
May 2025 |
Polycon Oy |
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| 13 |
T. Salminen |
Contract review with large language models |
Apr. 2025 |
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video |
| 14 |
E. Kohvakka |
The role of analyst sentiment in excess return forecasting, and its implications for investors |
Apr. 2025 |
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| 15 |
A. Sarkima |
Graph-based anomaly detection: Evaluating Logs2Graphs with non-benchmark logs |
Mar. 2025 |
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| 16 |
J. Naveed |
Optimized code generation in BIM with retrieval-augmented LLMs |
Feb. 2025 |
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| 17 |
P. Wiwatphonthana |
Machine Learning Assisted Dynamic Scheduling for Energy Efficient Serverless Cloud Workloads |
Jan. 2025 |
Ericsson Oy |
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| 18 |
Q. Luong |
Proof of Concept for FedRelax on Kubernetes: An Implementation Guide |
Jan. 2025 |
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| 19 |
P. Dang |
Model-Agnostic Personalized Federated Learning using Adaptive Client Selection |
Jan. 2025 |
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video |
| 20 |
L. Loukamo |
The effect of language on perceived ability to understand machine learning concepts |
Dec. 2024 |
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| 21 |
I. Tarpila |
Training Machine Learning Models for E-sports Spatiotemporal TimeSeries Forecasting |
Nov. 2024 |
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| 22 |
I. Lahtinen |
Binary classification of invoice documents based on value added tax |
Nov. 2024 |
KPMG Oy Ab |
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| 23 |
R. Kausiala |
Forecasting Retail Investor Fund Flow Using Machine Learning |
Nov. 2024 |
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video |
| 24 |
V. Toivonen |
Determining User Preference Profiles from Email And User Engagement Data |
Oct. 2024 |
Vibemetrics Oy |
video |
| 25 |
M. Hilvo |
The effect of privacy enhancing technologies on the quality of predictive models in healthcare |
Oct. 2024 |
VTT |
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| 26 |
A. Bhat |
Classifying Scam E-Commerce Shops with Supervised Learning |
Oct. 2024 |
F-Secure |
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| 27 |
A. Rodimov |
Security system based on object tracking by video stream |
Aug. 2024 |
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video |
| 28 |
A. Shuianova |
Kinship verification between two people by photos |
Aug. 2024 |
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| 29 |
J. Rantanen |
Large Language Models in Mental Health Support |
July 2024 |
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video |
| 30 |
R. Mård |
Backdoor attacks on large transformer-based regression model |
July 2024 |
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video |
| 31 |
A. Ghazal |
Zero-shot Machine Unlearning using GANs |
July 2024 |
Nokia |
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| 32 |
K. Nguyen |
Image Similarity Assessment for Product Quality Assurance |
July 2024 |
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| 33 |
D. Suman |
Deep Learning Methods for Demand Time Series Forecasting |
June 2024 |
Zalando |
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| 34 |
A. Manninen |
Spatiotemporal Traffic Accident Prediction Using Deep Learning Models |
May 2024 |
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video |
| 35 |
S. Hirvonen |
Comparison of data-driven models for building energy load forecasting |
May 2024 |
VTT |
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| 36 |
L. Ban |
Neural Motif Counting in Uncertain Graphs |
May 2024 |
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| 37 |
R. Virtanen |
Explainable AI Techniques in Trustworthy Object Detection |
May 2024 |
TietoEVRY Oyj |
video |
| 38 |
T. Kulokoski |
How well can Machine Learning teach Humans about Machine Learning? |
Mar. 2024 |
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video |
| 39 |
S. Facchini |
Prediction of fuel usage consumption in the airline industry |
Mar. 2024 |
Finnair |
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| 40 |
L. Veneranta |
Optimization of Web Page Advertisements using Contextual Bandits |
Jan. 2024 |
Sanoma Media |
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| 41 |
J. Li |
Empirical Emissions Modeling using Machine Learning |
Jan. 2024 |
aurobay.com |
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| 42 |
K. Izadi Garmaseh |
Frequency Offset Estimation Using Deep Learning |
Jan. 2024 |
Nokia |
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| 43 |
S. Chowdhury |
Computer vision-assisted safety alert system for industrial settings in private 5G networks |
Jan. 2024 |
TietoEVRY Oyj |
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| 44 |
T. Kontola |
Predicting User Web Behaviour with Machine Learning Methods |
Jan. 2024 |
Columbia Road Oy |
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| 45 |
R. Siljander |
Extreme gradient boosting methods for covariate forecasting of housing market demand in Finnish postal code areas |
Dec. 2023 |
Alma Talent Oy |
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| 46 |
J. Jäkärä |
From Candles to Ticks - Improving financial backtesting accuracy |
Dec. 2023 |
Aekos Trading Oy |
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| 47 |
X. Landa Oregi |
MLOps data ingestion pipeline for reciprocal benefit between customer and provider |
Nov. 2023 |
Huawei |
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| 48 |
T. Brumani |
Microservices-based autonomous anomaly detection for mobile network observability |
Sept. 2023 |
Ericsson Oy |
video |
| 49 |
G. Rivi |
Software Defined Networking Controlled Energy Optimization through Traffic Prediction on Microwave Access Network |
Sept. 2023 |
Ericsson Finland |
video |
| 50 |
Á. García Gutierrez |
Anomaly Detection on Osmosis Trades |
Sep. 2023 |
Numia Data |
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| 51 |
Z. Liu |
Deep Learning based method for Fire Detection |
Sept. 2023 |
Detectium |
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| 52 |
M. Bogdanova |
Contextual bandits for staffing in consulting companies: An exploration of personalized decision making |
Sept. 2023 |
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| 53 |
Z. Zhou |
Building information modeling connection recommendation based on machine learning using multimodal information |
Aug. 2023 |
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video |
| 54 |
Y. Sarcheshmehpour |
Application of Reinforcement Learning in Electrical Machine Design |
Aug. 2023 |
ABB Oy |
video |
| 55 |
L. Garcia Tejada |
Applying Machine Learning to Forecast Formula 1 Race Outcomes |
Aug. 2023 |
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video |
| 56 |
C. Segercrantz |
Experimental evaluation of record linkage algorithms in a secure banking environment |
Aug. 2023 |
Nordea Bank Oyj |
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| 57 |
H. Wang |
Material Capture and Generative Rendering with Phenomenological Reflectance Models |
Aug. 2023 |
Huawei |
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| 58 |
G. Jiang |
Parallel Training of Neural Networks in 6G L1 |
Aug. 2023 |
Nokia Oy |
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| 59 |
K. Lasocki |
Deep learning for continuous symbolic melody generation conditioned on lyrics and initial melodies |
Aug. 2023 |
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| 60 |
T. Vanhala |
Data-driven xVA exposure calculation for a portfolio of interest rate swaps |
May 2023 |
Nordea Markets |
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| 61 |
A. Agisheva |
Ethics in machine learning publications: Peer-review analysis using NLP methods |
May 2023 |
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| 62 |
R. Tikkanen |
Clustering fitness tracker data to correct interdevice differences in energy expenditure estimation |
May 2023 |
Fjuul |
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| 63 |
H. Vu |
Deep learning-based Mammography Image Segmentation |
Mar. 2023 |
Planmed |
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| 64 |
S. Johansson |
Classification of Purchase Invoices to Analytic Accounts with Machine Learning |
Jan. 2023 |
SprintIT |
video |
| 65 |
T. Sormunen |
Pallet Detection in Warehouse Environment |
Jan. 2023 |
Wartsila |
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| 66 |
J. Himanen |
Towards a data-driven circular economy: predicting material streams in the construction industry |
Jan. 2023 |
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| 67 |
B. Fazekas |
Distractive driver behaviour detection with spiked neural networks |
Nov. 2022 |
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| 68 |
T. Rahman |
Intrusion Detection system based on Deep Learning |
Aug. 2022 |
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| 69 |
T. Gyabaah |
Artificial intelligence to support NFTs creation: Comparison of Machine learning algorithms to detect fraud in artwork |
Jul. 2022 |
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| 70 |
J. Lillfors |
Networked Federated Learning |
Jul. 2022 |
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| 71 |
Á. C. Barcsa-Szabó |
Feature-based Approaches for Ethical News Personalization |
Jul. 2022 |
Sanoma Media Finland |
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| 72 |
C. Molinero Ranera |
Multi-label classification of a hydraulic system using Machine Learning |
Jul. 2022 |
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video |
| 73 |
V. Petrutiu |
Exploring Transformers and Degradation Methods in the Super Resolution Field |
Jul. 2022 |
Huawei |
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| 74 |
P. Truong |
Crown-of-Thorns Starfish detection by state-of-the-art YOLOv5 |
Jul. 2022 |
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| 75 |
Y. Huang |
Text analysis of novel coronavirus pneumonia based on federal deep learning |
June 2022 |
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| 76 |
C. Ozen |
A collaborative approach for large-scale Electricity consumption using Federated Learning |
June 2022 |
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| 77 |
P. Prinsén |
Robust Gas pressure control using Neural Networks |
Jan. 2022 |
Wartsila Finland Oy |
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| 78 |
E. Hattula |
Transfer Learning Technology for Building Extraction from Orthophotos and Open-Source Data |
Jan. 2022 |
National Land Survey of Finland |
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| 79 |
A. Channabasaiah |
Applying machine learning methods to predict taxi pickups using historical taxi data |
Jan. 2022 |
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video |
| 80 |
R. Hellström |
Aspect Based Sentiment Analysis in Finnish |
Jan. 2022 |
Crowst Oy |
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| 81 |
A. Orre |
Pedestrian movement analysis from drone perspective |
Dec. 2021 |
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| 82 |
P. Vijayakrishnan |
Semi-supervised machine learning techniques for infant motility classification |
Oct. 2021 |
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| 83 |
K. Ariko |
Increasing the safety in the proximity of the mobile working machines: a study of detecting people |
Oct. 2021 |
Epec Oy |
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| 84 |
M. Uutaniemi |
Extraction of labeled fields from images of structured documents |
Aug. 2021 |
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| 85 |
K. Kutlu |
Machine Learning based Chaos Engineering for Cloud-Native Microservice Architectures |
Aug. 2021 |
Ericsson |
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| 86 |
M. Leinonen |
Federated Multi-task Learning over Networked Data |
June 2021 |
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| 87 |
J. Seppälä |
Application of machine learning to link click predictions in Facebook Family of Apps advertising |
2021 |
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| 88 |
M. Afteniy |
Predicting time series with Transformer |
May 2021 |
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| 89 |
Z. Mohammadi |
Better Utilization of Relational Data in Machine Learning |
May 2021 |
Lamia Oy |
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| 90 |
T. Nguyen |
Applying Machine Learning to Develop Black-box Control Model of Active Double-Skin Facade |
Jan. 2021 |
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| 91 |
P. Pyrrö |
AIR: Aerial Inspection RetinaNet for Land Search and Rescue Missions |
Jan. 2021 |
Accenture |
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| 92 |
T. Kokkonen |
Classifying Restaurant Menu Items With Supervised Learning |
Jan. 2021 |
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video |
| 93 |
I. Vikström |
Deep reinforcement learning approach for HVAC control |
Dec. 2020 |
TietoEVRY Oyj |
video |
| 94 |
D. Tokmurzina |
Road marking condition monitoring and classification using deep learning for city of Helsinki |
Oct. 2020 |
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| 95 |
C. Dikmen |
Application of Contextual Bandits Models in a Supervised Learning Setting |
Aug. 2020 |
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| 96 |
J. Laiho |
Recognizing Thoughts from Bioelectric Patterns? A Brain-Computer Interface with Deep Learning |
Aug. 2020 |
Accenture Liquid Studio (NL) |
video |
| 97 |
X. Zhang |
Diagnostic and Prognostic Analysis Optimization of Field Problems for EV Charging Stations |
Aug. 2020 |
ABB |
video |
| 98 |
M. Mishin |
Anomaly Detection Algorithms and Techniques for Network Intrusion Detection Systems |
Aug. 2020 |
Ericsson |
video |
| 99 |
K. Klemets |
Forecasting Hourly Parking Occupancy with Multiple Seasonalities |
Aug. 2020 |
City of Helsinki |
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| 100 |
T. Valentijn |
The Practical Applicability of a CNN for Automated Building Damage Assessment |
June 2020 |
Red Cross NL |
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| 101 |
T. Hämmäinen |
Clustering IoT devices for network intrusion detection systems |
May 2020 |
Ericsson |
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| 102 |
J. Moisala |
Optimizing the mark-up of foreign exchange derivative contracts using machine learning |
May 2020 |
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| 103 |
J. Nieminen |
Framework for application of machine learning algorithms in telecommunications |
Mar. 2020 |
Nokia Oy |
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| 104 |
L. Kolehmainen |
A web scraping system for extracting news articles |
Dec. 2019 |
Vainu Finland Oy |
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| 105 |
M. Torres Porta |
Anti-Money Laundering system based on customer behavior |
Aug. 2019 |
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| 106 |
T. Wiro |
Market influence on purchase prices in procurement |
June 2019 |
Sievo |
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| 107 |
D. Baad |
Automatic Job Skill Taxonomy Generation For Recruitment Systems |
June 2019 |
VXT Research Oy |
|
| 108 |
J. Eskonen |
Deep Reinforcement Learning in Automated User Interface Testing |
May 2019 |
Ericsson |
|
| 109 |
A. Moskalev |
Demand forecasting for fast-moving products in grocery retail |
May 2019 |
Relex |
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| 110 |
K. Karapetyan |
Process Mining of Automation Services with Long Short-Term Memory Neural Networks |
March 2019 |
Posti Group Oyj |
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| 111 |
H. Ambos |
Semi-Supervised Learning over Complex Networks |
Mar. 2019 |
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| 112 |
J. Kahles Bastida |
Applying Machine Learning to Root Cause Analysis in Agile CI/CD Software Testing Environments |
Jan. 2019 |
Ericsson |
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| 113 |
A. Shehata |
Cellular Network Average User Throughput-Downlink Prediction by Machine Learning |
Dec. 2018 |
Nokia |
|
| 114 |
O. Abramenko |
Graph signal sampling via reinforcement learning |
Nov. 2018 |
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| 115 |
M.O. Nasir |
Supervised Learning in Lighting Control Systems |
Oct. 2018 |
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| 116 |
D. Wu |
Unsupervised Learning for Lighting Control System |
Oct. 2018 |
Helvar Oy |
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| 117 |
N. Pokhrel |
Drone Obstacle Avoidance and Navigation Using Artificial Intelligence |
May 2018 |
Nokia |
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| 118 |
D. Koskenniemi |
Do financial networks improve the explanatory power of the Fama-French factors? A comparison of propagation algorithms on stock market returns |
Mar. 2018 |
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| 119 |
S. Basirian Jahromi |
Compressed Sensing for Big Data Over Complex Networks |
Jan. 2018 |
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| 120 |
A. Mara |
A Comparative Analysis of Graph Signal Recovery Methods for Big Data Networks |
Oct. 2017 |
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| 121 |
Y. Gao |
Graphical Model Selection in Big Data Application |
Dec. 2016 |
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