
Where is the Grass Greener? Revisiting Generalized Policy Iteration for Offline Reinforcement Learning
The performance of stateoftheart baselines in the offline RL regime v...
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Conditional Neural Relational Inference for Interacting Systems
In this work, we want to learn to model the dynamics of similar yet dist...
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Learned transform compression with optimized entropy encoding
We consider the problem of learned transform compression where we learn ...
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PhysicsIntegrated Variational Autoencoders for Robust and Interpretable Generative Modeling
Integrating physics models within machine learning holds considerable pr...
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Kanerva++: extending The Kanerva Machine with differentiable, locally block allocated latent memory
Episodic and semantic memory are critical components of the human memory...
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ProxyFAUG: Proximitybased Fingerprint Augmentation
The proliferation of datademanding machine learning methods has brought...
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Analysing the DataDriven Approach of Dynamically Estimating Positioning Accuracy
The primary expectation from positioning systems is for them to provide ...
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Goaldirected Generation of Discrete Structures with Conditional Generative Models
Despite recent advances, goaldirected generation of structured discrete...
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Lipschitzness Is All You Need To Tame Offpolicy Generative Adversarial Imitation Learning
Despite the recent success of reinforcement learning in various domains,...
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Improving VAE generations of multimodal data through datadependent conditional priors
One of the major shortcomings of variational autoencoders is the inabili...
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A Reproducible Comparison of RSSI Fingerprinting Localization Methods Using LoRaWAN
The use of fingerprinting localization techniques in outdoor IoT setting...
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A Reproducible Analysis of RSSI Fingerprinting for Outdoor Localization Using Sigfox: Preprocessing and Hyperparameter Tuning
Fingerprinting techniques, which are a common method for indoor localiza...
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HyperKG: Hyperbolic Knowledge Graph Embeddings for Knowledge Base Completion
Learning embeddings of entities and relations existing in knowledge base...
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Learning by stochastic serializations
Complex structures are typical in machine learning. Tailoring learning a...
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Variational Saccading: Efficient Inference for Large Resolution Images
Image classification with deep neural networks is typically restricted t...
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Continual Classification Learning Using Generative Models
Continual learning is the ability to sequentially learn over time by acc...
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SampleEfficient Imitation Learning via Generative Adversarial Nets
Recent work in imitation learning articulate their formulation around th...
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Structured nonlinear variable selection
We investigate structured sparsity methods for variable selection in reg...
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Largescale Nonlinear Variable Selection via Kernel Random Features
We propose a new method for input variable selection in nonlinear regres...
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Learning Predictive Leading Indicators for Forecasting Time Series Systems with Unknown Clusters of Forecast Tasks
We present a new method for forecasting systems of multiple interrelated...
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Forecasting and Granger Modelling with Nonlinear Dynamical Dependencies
Traditional linear methods for forecasting multivariate time series are ...
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Lifelong Generative Modeling
Lifelong learning is the problem of learning multiple consecutive tasks ...
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Regularising Nonlinear Models Using Feature Sideinformation
Very often features come with their own vectorial descriptions which pro...
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Learning Leading Indicators for Time Series Predictions
We consider the problem of learning models for forecasting multiple time...
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TwoStage Metric Learning
In this paper, we present a novel twostage metric learning algorithm. W...
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Learning Heterogeneous Similarity Measures for HybridRecommendations in MetaMining
The notion of metamining has appeared recently and extends the traditio...
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A metric learning perspective of SVM: on the relation of SVM and LMNN
Support Vector Machines, SVMs, and the Large Margin Nearest Neighbor alg...
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Alexandros Kalousis
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