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Explore a wide range of free and certified Memory online courses. Find the best Memory training programs and enhance your skills today!
Explore JVM memory management, common OutOfMemoryError causes, and techniques for detecting and resolving memory leaks in Java applications. Learn from real-world scenarios and practical tools.
Speculative execution attacks can bypass memory corruption defenses such as stack canaries, control flow integrity, and memory-safe languages.
Unveiling a critical x86 design flaw allowing privilege escalation, exploring forgotten backdoors, and demonstrating how to exploit vulnerabilities in processor architecture.
Explore Flash memory reverse engineering techniques, including direct interaction, reprogramming, and file system analysis. Learn to handle meta information, deal with bad blocks, and leverage journaling file systems for deeper insights.
Learn to spot memory inefficiency in Java applications and reduce allocations that can hurt throughput and tail latency.
A live demo and war stories show how hidden memory inefficiency in Java can surface as lower throughput and more frequent tail latency.
A demonstration of how shared-page memory deduplication can expose remote systems to attacks despite protections that separate security domains.
Examines how Linux kernel tracing infrastructure can close a blind spot that leaves attackers undetected in memory-forensics research.
Explains how neuronal engrams encode memories, how excitability shapes which neurons join them, and how distributed traces support recall and memory linking.
A technical talk on SRAM-based in-memory computing, from analog memory-array circuits and ADCs to accelerator architectures for energy-efficient AI inference.
Set up LPDDR4/DDR4 memory simulations in Keysight ADS, from importing a PCB and defining its stackup to analyzing eye results and troubleshooting anomalies.
Train 256×256 StyleGAN2 ADA models on an 8GB RTX 3060 Ti by tuning memory, metrics, snapshots, and installation settings.
Code an LSTM from scratch, train it with PyTorch Lightning, and compare it with PyTorch’s built-in nn.LSTM while tracking results in TensorBoard.
An intuitive explanation of LSTM networks, showing how memory paths address vanishing and exploding gradients in long sequences.
Explores Windows reparse-point vulnerabilities, from a logic flaw that bypasses mitigations to a newly exposed memory-corruption attack surface.
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