Multi-party Computation I - Session 109
Explore the fundamentals and applications of Multi-party Computation, a cryptographic protocol enabling secure collaborative computations while preserving data privacy.
Multiparty Computation Advances - Asiacrypt 2022 Session 2
Explore advanced topics in multiparty computation at Asiacrypt 2022, featuring cutting-edge research and insights from leading experts in cryptography.
Distributed Algorithms
Explore cutting-edge distributed algorithms in cryptography, discussing recent advancements and their implications for secure, decentralized systems.
Secure Multiparty Computation - Session II
Explore advanced concepts and recent developments in secure multiparty computation, focusing on cutting-edge research presented at Crypto 2022.
Secure Multiparty Computation - Session I
Explore cutting-edge developments in secure multiparty computation, a cryptographic technique enabling collaborative data analysis while preserving privacy and confidentiality.
Multi-Party Computation - Session 2
Explore advanced concepts in multi-party computation at TCC 2023, featuring cutting-edge research presentations and discussions on secure distributed computing protocols.
Multiparty Computation Advances - Session 1
Explore cutting-edge developments in multiparty computation at this TCC 2023 session, featuring expert presentations on advanced cryptographic protocols and secure distributed computing.
Truly Universal Compute - Using Bacalhau to Deploy Jobs Cross Region, Cross Cloud and to the Edge
Explore Bacalhau, a unified platform for managing distributed compute jobs across regions, clouds, and edge devices, addressing challenges in data availability, scalability, and security.
Fundamentals of Privacy-Preserving Federated Learning
Explore privacy-preserving techniques in federated learning, focusing on data protection and collaborative model training across distributed datasets.
Running Distributed TensorFlow on DC/OS
Learn to run distributed TensorFlow on DC/OS, addressing challenges in large-scale machine learning. Explore framework design, live demo, and practical implementation for efficient model training on your infrastructure.
Building a Big Data Collection and Processing System
Explore building a system for collecting, storing, and processing massive amounts of data using Apache Mesos and Hadoop, with a focus on video surveillance applications.
Distributed Deep Learning on Apache Mesos with GPUs and Gang Scheduling
Explore distributed deep learning on Apache Mesos, leveraging GPU clusters for efficient model training in self-driving cars, trip forecasting, and fraud detection at UBER.
Fault Tolerant Frameworks - Making Use of CNI Without Docker
Explore building highly available, performant Mesos frameworks using universal containerizer and CNI without Docker. Learn about Go implementation, V1 streaming API, and accompanying SDK.
How Linux Foundation is Changing the Machine Learning World
Explore Linux Foundation's initiatives in AI, including open-source projects like Acumos AI and Horovod, aimed at reducing fragmentation and fostering collaboration in machine learning development.
Multi-Cloud Machine Learning Data and Workflow with Kubernetes
Explore building a multi-cloud ML platform using Kubernetes for autonomous vehicles, addressing data management, scheduling, and hardware support across diverse environments.
Angel 3.0 - A Full Stack Machine Learning Platform
Explore Angel 3.0, a comprehensive machine learning platform featuring auto feature engineering, hyperparameter tuning, model serving, and PyTorch integration for enhanced graph embedding and GNN algorithms.
Large Scale Distributed Deep Learning on Kubernetes Clusters
Explore distributed deep learning deployment on Kubernetes, comparing tf-operator and mpi-operator for TensorFlow training jobs, and optimizing resource utilization for better economics in machine learning tasks.
IPVM Community Call - Content-Addressed Computation in IPFS
Explore IPVM's content-addressed computation for IPFS, covering calling conventions, distributed scheduling, and more in this implementer-focused community discussion.
New Era in Distributed Computing with Blockchains and Databases
Explore the emerging era of distributed computing with blockchains and databases, focusing on commercial applications, ongoing projects, and open research problems in this field.
Research in Data Management - Challenges and Projects
Explore cutting-edge data management research, including VR/AR video databases, in-memory storage optimization, MapReduce frameworks, cardinality estimation, bias detection in OLAP queries, and automated query reasoning.
Accelerating AI and ML: Architectures and Systems for Efficient Computing
Exploring domain-specific accelerators for AI/ML, focusing on high-performance computing solutions and innovative frameworks to optimize large-scale distributed deep learning systems.