Writing
Notes and deep-dives — bridging theory and the systems I build.
- · 11 min read
RAG That Renders the Diagram: Outline-Aware Chunking and Image-Grounded Answers
How I built a hallucination-resistant RAG over a large technical-document corpus: chunk along the author's heading outline, embed with that outline as context, and treat images as first-class chunks with a deterministic verifier.
EngineeringRAGRetrievalLLMSearchDocument AIRead - · 10 min read
The real cost of best-arm identification isn't the arms — it's the clusters
When arms come with a similarity graph and rewards vary smoothly over it, best-arm identification's binding cost drops from the number of arms to the number of clusters.
multi-armed banditspure explorationbest-arm identificationgraph signal processinglearning theoryRead - · 12 min read
The Branch Is the Variant: Zero-Copy, Privacy-Safe Test Data on a Versioned Lake
How a versioned data lake made the branch itself the test-data variant — zero-copy generation, blobstore-native metadata, and in-database hooks as the output channel.
EngineeringData InfrastructurelakeFSSystem DesignKubernetesPrivacyRead - · 10 min read
Why You Can Start Gradient Descent Anywhere — Even on an NP-Hard Recovery Problem
With order-n complex Gaussian quadratic measurements, recovering a vector up to phase becomes both identifiable and solvable by gradient descent from any starting point — two faces of one geometric condition.
phase retrievalnonconvex optimizationquadratic feasibilitysample complexityoptimization landscapeRead - · 11 min read
One Coin Flip That Spans Fast Search and Cheap Search
Two robotic-search strategies optimize opposite costs; randomly interleaving them with one tunable coin lets you slide between "find targets now" and "spend the least energy."
multi-armed-banditsmulti-agent-searchadaptive-sensingroboticsthresholding-banditRead - · 10 min read
Generate the Spectrum, Don't Store It: Physics as a Trainable Prior for Unmixing
Why a 100-year-old optical-physics model, made differentiable, beats data-hungry neural nets at hyperspectral unmixing exactly when labeled data is scarce.
hyperspectral unmixingdifferentiable programmingremote sensinginverse renderingphysics-based MLspectroscopyRead - · 9 min read
Learn the Calendar Once, Not the Leader Every Week
Why amnesiac non-stationary bandits keep paying to rediscover a periodic optimum, and how a number-theoretic period estimator lets the policy learn the cycle once instead.
Multi-Armed BanditsNon-Stationary LearningRamanujan Periodicity TransformSignal ProcessingRegret MinimizationRead - · 10 min read
Design the Algorithm First, Then Reverse-Engineer the Utility It Secretly Maximizes
A trick for games whose natural Nash equilibrium is intractable: hand-build the adaptive rule with the right selfish reflexes, then discover the well-behaved utility it implicitly optimizes.
game theorylearning in gamesNash equilibriumdistributed algorithmscongestionwirelessRead - · 6 min read
Projected Gradient Descent with Skipping
Exploring an interesting optimization technique that skips projection steps to potentially improve convergence in constrained convex optimization.
optimizationgradient-descentresearchmathematicsRead