Contextual Word Embeddings Clustering through Multiway Analysis: A Comparative Study
Transferable Deep Metric Learning for Clustering
Spatial Graph Convolution Neural Networks for Water Distribution Systems
Data-Centric Perspective on Explainability versus Performance Trade-off
Towards Data Science Design Patterns
Diverse Paraphrasing with Insertion Models for Few-Shot Intent Detection
LEMON: Alternative Sampling for More Faithful Explanation through Local Surrogate Models
GASTeN: Generative Adversarial Stress Test Networks
Learning Permutation-Invariant Embeddings for Description Logic Concepts
Diffusion Transport Alignment
Mind the Gap: Measuring Generalization Performance Across Multiple Objectives
Effects of Locality and Rule Language on Explanations for Knowledge Graph Embeddings
Shapley Values with Uncertain Value Functions. -Revised Conditional t-SNE: Looking Beyond the Nearest Neighbors
On the Change of Decision Boundary and Loss in Learning with Concept Drift
AID4HAI: Automatic Idea Detection for Healthcare-Associated Infections from Twitter, A Framework based on Active Learning and Transfer Learning
Explanations for Itemset Mining by Constraint Programming: A Case Study using ChEMBL data
Translated Texts Under the Lens: From Machine Translation Detection to Source Language Identification
Geolet: An Interpretable Model for Trajectory Classification
An investigation of structures responsible for gender bias in BERT and DistilBERT
Discovering diverse top-k characteristic lists
Online Influence Forest for Streaming Anomaly Detection
APs: a proxemic framework for social media interactions modeling and analysis
User Authentication via Multifaceted Mouse Movementsand Outlier Exposure
Explaining Black Box Reinforcement Learning Agents Through Counterfactual Policies
A GNN-based Architecture for Group Detection from spatio-temporal Trajectory Data
Discovering Rule Lists with Preferred Variables
Don’t Start Your Data Labeling from Scratch: OpSaLa - Optimized Data Sampling Before Labeling
The Other Side of Compression: Measuring Bias in Pruned Transformers
Dropping incomplete records is (not so) straightforward
Meta-Learning for Automated Selection of Anomaly Detectors for Semi-Supervised Datasets
Should We Consider On-Demand Analysis in Scale-Free Networks?
ROCKAD: Transferring ROCKET to whole time series anomaly detection
Out-of-Distribution Generalisation with Symmetry-Based Disentangled Representations
Forecasting Electricity Prices: an Optimize then Predict-based approach
A Similarity-Guided Framework for Error-Driven Discovery of Patient Neighbourhoods in EMA Data
QBERT: Generalist Model for Processing Questions
On Compositionality in Data Embedding.