Devdatt Dubhashi
Mina huvudintressen är inom design och analys av randomiserade algoritmer, maskininlärning för Big Data och beräkningsbiologi.
Visar 62 publikationer
Recovery Bounds on Class-Based Optimal Transport: A Sum-of-Norms Regularization Framework
Using Satellite Images and Deep Learning to Measure Health and Living Standards in India
Do Kernel and Neural Embeddings Help in Training and Generalization?
Hybrid Quantum-Classical Heuristic to Solve Large-Scale Integer Linear Programs
A synthetic population of Sweden: datasets of agents, households, and activity-travel patterns
Can Universities Combat the 'Wrong Kind of AI'?
Synthetic Sweden Mobility (SySMo) Model Documentation
Analysis of Knowledge Transfer in Kernel Regime
Controlling gene expression with deep generative design of regulatory DNA
Pragmatic Reasoning in Structured Signaling Games
Thompson Sampling for Bandits with Clustered Arms
Melting together prediction and inference
Learning Approximate and Exact Numeral Systems via Reinforcement Learning
Accelerated proximal incremental algorithm schemes for non-strongly convex functions
Mathematical Models for COVID-19 Pandemic: A Comparative Analysis
A reinforcement-learning approach to efficient communication
Bayesian optimization in ab initio nuclear physics
A Non-Convex Optimization Approach to Correlation Clustering
Clustering by Sum of Norms: Stochastic Incremental Algorithm, Convergence and Cluster Recovery
Thompson Sampling for Stochastic Bandits with Graph Feedback
Extractive summarization by aggregating multiple similarities
Classifying large graphs with differential privacy
Visions and open challenges for a knowledge-based culturomics
Neural context embeddings for automatic discovery of word senses
Weighted theta functions and embeddings with applications to Max-Cut, clustering and summarization
Learning with similarity functions on graphs using matchings of geometric embeddings
Federated clouds for biomedical research: Integrating OpenStack for ICTBioMed
Extractive Summarization using Continuous Vector Space Models
Global graph kernels using geometric embeddings
Mining semantics for culturomics: towards a knowledge-based approach
Lovasz θ, SVMs and applications
Computational approaches for reconstruction of time-varying biological networks from omics data
DLOREAN: Dynamic Location-aware Reconstruction of multiway Networks
Lovasz theta function, SVMs and Finding Dense Subgraphs
Entity disambiguation in anonymized graphs using graph kernels
The Lovász v function, SVMs and finding large dense subgraphs
Scalable multi-dimensional user intent identification using tree structured distributions
NETGEM: Network Embedded Temporal GEnerative Model for gene expression data
Adaptive Dynamics of Realistic Small-World Networks
Bridging the gap between systems biology and medicine
A note on conditioning and stochastic domination for order statistics
Distributed approximation algorithms via LP-duality and randomization
Probabilistic analysis for a multiple depot vehicle routing problem
positiv influence and negative dependence
Localized techniques for broadcasting in wireless sensor networks.
Distributed Approximation Algorithms via Randomization
Randomization in Constraint Programming for Airline Planning
Probabilistic Analysis for a Multiple Depot Vehicle Routing Problem.
Fast distributed algorithms for (weakly) connected dominating sets and linear-size skeletons
Irrigating ad hoc networks in constant time
Connectivity Properties of Bluetooth Wireless Networks
Fast distributed algorithms for (weakly) connected dominating sets and linear-size skeletons
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Visar 16 forskningsprojekt
Public policies and indicators for well-being and sustainable development
Quantumstack: Programmering av kvantdatorn
Yata – Intelligenta system för att förbättra och stödja undervisning
Deep Reinforcement Learning: Principles and Applications in Cognitive Science and Networks (
Grundorsaksanalys av kvalitetsavvikelser vid tillverkning med användning av maskininlärning (GOA-ML)
Centre of excellence for Global Systems Science (CoeGSS)
ACE: Approximativa algoritmer och datorsystem
Big data Analytics and Infrastructure for Business Intelligence, Biomedicine and Health
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Informationsdriven säker Business Intelligence (DataBIN)