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New GPUThor Rowhammer Defeats ECC on NVIDIA RTX A6000 to Gain Host Root Access

University of Toronto researchers present GPUThor, a Rowhammer attack that defeats ECC on NVIDIA RTX A4000-A6000 GDDR6 GPUs and achieves host root access.

GPUThor uses non-uniform hammering to bypass Target Row Refresh and overcome SECDED ECC on NVIDIA Ampere workstation GPUs with GDDR6 memory, inducing 72,000 to 377,552 bit flips per gigabyte across RTX A6000, A5000, A4500, and A4000 cards. Triple-bit silent data corruption enables host privilege escalation to root with the IOMMU enabled, reusing GPUBreach page-table corruption techniques, and double-bit DUEs allow escalation when the IOMMU is disabled during a ~10 ms lazy-service window. The attack cut end-to-end escalation time on the A6000 from 21.9 hours to 1.1 minutes. Reported to NVIDIA, Google, Microsoft, and AWS on April 29, 2026; findings were embargoed until August 25, 2026, and no CVE identifier was assigned.

The Hacker News · 8d agoResearch1

Hackers Abuse Google Sheets as C2 in ClickFix Attacks to Steal Cryptocurrency

Cisco Talos tracks a ClickFix crypto-theft campaign using Google Sheets as C2 to swap deposit addresses in Chrome.

Cisco Talos uncovered a cryptocurrency theft campaign that abuses Google Sheets and the Google Visualization API as a covert C2 channel, delivering obfuscated JavaScript into victims' Chrome browser sessions via ClickFix-style social engineering. Victims are lured with a fake "API Logic Flaw" report promising 25-38% bonuses on SimpleSwap and SwapZone swaps; the injected payload acts as a browser-based web skimmer that replaces deposit addresses, overrides the fetch API, and hijacks the clipboard. Later variants use the legitimate Tampermonkey extension with a user script for persistence without OS-level compromise. Talos identified 49 Bitcoin wallets, with 24 reused addresses receiving about 0.159 BTC (~$10,000) before mixing through more than 3,000 addresses.

GBHackers · 7d agoPhishing & fraud in the wild

Hamming Ideals and Grobner Bases for ISD-like Syndrome Decodingnew

Researchers combine Grobner bases with Information Set Decoding for syndrome decoding, testing feasibility against Classic McEliece NIST Category 1 parameters.

The paper proposes GBDecode, an ISD-like decoding algorithm that fixes only a subset of an information set and solves the resulting multivariate nonlinear systems via MultiSolve, which replaces one Grobner basis computation with many computations on simpler systems. Hamming weight constraints are reformulated using elementary symmetric functions and Lucas' identity factorizations to bound equation degree. Experiments on random binary linear codes use parameters matching the NIST Security Category 1 set of the Classic McEliece cryptosystem, assessing practical feasibility rather than breaking the scheme.

arXiv cs.CR · 12h agoResearch

Search results are sending people to fake Bitrefill checkouts

Scam sites impersonating Bitrefill's crypto checkout appear in search results, tricking victims into sending up to $1,990 in crypto directly to scammers.

Malwarebytes documents a cluster of lookalike domains copying Bitrefill's gift card checkout, surfaced via search engine results rather than email. Victims choose an amount up to $1,990 and pay in Bitcoin, Ethereum, USDC, USDT, Solana, or Litecoin to scammer-controlled addresses, with no recourse since crypto payments are irreversible. Domains use typosquatting and Punycode/IDN homoglyph tricks, and the fake sites run commercial analytics software to measure and optimize victim conversion. Bitrefill's security team is working with takedown specialists to remove the sites.

Malwarebytes Labs · 1d agoPhishing & fraud

A Princeton Researcher Proposes Recurrent Looped Transformer (RLT) that Carries Decoder State across Every Token, Fixing 96 Blocks per Token with Unbounded Temporal Depth

Princeton researcher Yifan Zhang proposes Recurrent Looped Transformer, carrying full decoder state across every token for unbounded temporal depth.

Yifan Zhang's technical report defines the Recurrent Looped Transformer (RLT), pairing a causal encoder with a recurrent decoder whose final output and layerwise sliding-window attention cache carry into every subsequent token with no prompt-response boundary reset. The reference configuration ties 48 encoder and 48 decoder layers, executing 96 logical blocks per token while the state path grows to 48t blocks after t tokens at fixed per-token compute. The report details RL replay contracts that rebuild all states under current parameters and exact prefix snapshots for multi-turn serving, but explicitly reports no measured efficiency, reasoning quality, or scaling results.

MarkTechPost · 3d agoAI research1

Operational Roles of QRNG-Derived Quantum Entropy in Bitcoin Proof-of-Work Architectures

arXiv study finds quantum-random entropy adds no Bitcoin PoW success advantage but helps assurance in fault and provenance scenarios.

The paper shows replacing classical entropy with QRNG output does not change honest Bitcoin proof-of-work success probability when candidate headers remain distinct. It introduces a reproducible benchmark measuring an entropy-efficiency factor and a reboot-diversity index, finding QRNG value only in assurance-oriented scenarios involving correlated restart faults, namespace reuse, and entropy provenance. Validation is simulation-based, with hardware-in-the-loop testing identified as future work.

arXiv cs.CR · 12d agoResearch

Hackers Abuse Google Sheets to Hijack Crypto Wallet Addresses in ClickFix Attacks

Cisco Talos details a crypto-theft ClickFix campaign abusing Google Sheets to swap wallet addresses, with about $10,000 in observed Bitcoin losses.

Cisco Talos tracks a ClickFix-style campaign that tricks cryptocurrency traders into pasting JavaScript into Chrome's address bar or a Tampermonkey extension, promising fake bonuses on SwapZone and SimpleSwap. The loader pulls obfuscated JavaScript from cells in a public Google Sheet via the Visualization API, then behaves like a web skimmer, rewriting deposit addresses on screen, in web responses, and in the clipboard. Researchers counted 49 attacker-controlled Bitcoin addresses, with 24 receiving a combined 0.159 BTC, roughly $10,000, by early August 2026. A Tampermonkey variant re-injects the payload on every return visit, giving the attackers persistence despite takedown efforts.

Cyber Security News · 7d agoPhishing & fraud in the wild

Fraudsters steal $6 million from Tectonic crypto platform after inflating token price

Attackers inflated Tectonic's Tonic token price 100x in 20 minutes and borrowed $74 million against it, stealing $6 million before Cronos halted activity.

Attackers manipulated the price of Tectonic's thinly traded Tonic token, raising it more than 100-fold in 20 minutes, then used the inflated tokens as collateral to borrow assets in an attempted $74 million theft. About $6 million left the platform; Cronos halted blockchain activity and later restored roughly $69 million in frozen funds via an on-chain rollback. Tectonic plans a phased reopening and a postmortem. TRM Labs says market manipulation now accounts for one in eight crypto hacks, with 32 incidents in 2026, and compares the case to the 2022 Mango Markets manipulation that led to a criminal conviction.

The Record · 16d agoPhishing & fraud

No Bit Left Behind: Using Brute-Force Lifting to Achieve Fully Static Binary Recompilation

Prototype binary lifter brute-force lifts every byte offset of x86-64 binaries to LLVM IR, enabling fully static cross-ISA recompilation without runtime support.

The paper presents a fully static, whole-program binary lifting system that treats every byte offset as a potential branch target, constructing a superset control flow graph that conservatively contains all feasible control flows. Statically unresolvable computed branches are reduced to lookups in a dispatch table pointing to translated control flow paths, eliminating runtime translation machinery on the target machine. A prototype recompiles x86-64 binaries to LLVM IR with no code/data heuristics and achieves fully static cross-compilation to AArch64 using unmodified LLVM backends.

arXiv cs.CR · 2d agoResearch1

Hardware Fingerprinting FTQC via Quantum Decoder Timing

Quantum decoder timing on IBM Heron processors forms a side channel enabling device fingerprinting with 89% accuracy and workload inference.

The work demonstrates that wall-clock syndrome-decoding times on fault-tolerant quantum computers constitute a novel hardware side channel. Using per-shot decoder timings from three IBM Heron processors collected over 68 days, a passive observer can reconstruct detector-firing distributions, estimate logical error rate, infer code distance, and fingerprint the specific device with up to 89% accuracy versus 33% for random guessing. Noisy simulation based on Google's 105-qubit Willow processor distinguishes nine surface-code patches at 81% accuracy, showing the channel persists across vendors and code families.

arXiv cs.CR · 6d agoResearch

Breaking the 1.58-bit Barrier for Ternary LLMs

An arXiv paper claims a method that breaks the 1.58-bit barrier for ternary large language models.

The arXiv preprint 2609.16338, titled 'Breaking the 1.58-bit Barrier for Ternary LLMs,' presents research on ternary-weight large language models, which use roughly 1.58 bits per weight. The source text contained only the title and Hacker News engagement data (56 points, no comments), so further technical details are not available.

You've Got a BUD in Me: Authenticated Reads from Per-Block Write Logs

Researchers propose BUD, per-block write-log digests enabling blockchain validators to serve historical membership and exclusion proofs far cheaper than state-wide tries.

The paper introduces Block Update Digests (BUD), which authenticate each block's write log with predecessor pointers, plus a SuperBUD and exponential hierarchy to turn long unchanged intervals into short proofs. Soundness against adversarial provers and up to f Byzantine validators is proven under archive, attestation, and committee evidence assumptions. Benchmarks show a 50x state-size increase raises the base-BUD path only 1.24x versus 3.1x for in-memory and 69.5x for disk-backed Merkle Patricia tries, with read payloads below 800 bytes and p99 warm verification at 146 microseconds.

arXiv cs.CR · 6d agoResearch

Privacy Failure in Split-LLM Training, The Returned Gradient Nullifies the Decoys

Researchers show split-LLM training leaks privacy via zero-valued gradients on decoy rows, exposing which activations are real despite passing forward-channel checks.

A systems-security case study of a two-node split-LLM training setup found that the returned output gradient from an Untrusted Cloud Node is exactly zero for decoy rows, revealing which rows are real. Across nine seeds, zero patterns identified real rows in 4,096 of 4,096 frames per run, and an attack on frame contents recovered 0.65 to 1.50 percentage points of extra tokens over a baseline. Both datasets passed forward-channel privacy and quality checks but failed once the returned gradient was included. Row-wise gradient clipping and noise closed the leak for roughly 0.01 nats of held-out cross-entropy, though five unmeasured attack classes remain.

How Lossless Is Lossless Speculative Decoding? The Role of Numerical Precision in Orthrus

Reproduction study finds Orthrus speculative-decoding trajectories match the reference model in only ~45% of cases under BF16, but 100% under FP32.

Researchers independently reproduced Orthrus, a hybrid autoregressive-diffusion architecture claiming lossless speculative decoding via intra-model consensus, testing exact trajectory matching on 1,190 prompts across 12 domains. Under BF16, exact matching occurred in only 45% of cases for the authors' checkpoint and 43% for an independently trained model, with matching probability strongly tied to reference-model response-conditional perplexity. Despite trajectory divergence, downstream lm-eval-harness benchmarks showed no systematic degradation, while FP32 evaluation yielded exact matching on all prompts.

Hugging Face daily papers · 3d agoAI research1

Analog Pin Directionality as an Exfiltration Attack Surface in Mixed-Signal ICsnew

Researchers demonstrate exfiltration through nominally input-only analog pins in mixed-signal ICs, recovering data at 10 kbps on a 55nm PPG front-end.

The paper identifies a directionality-based attack class in analog/mixed-signal (AMS) ICs where data-dependent circuit-offset modulation converts a nominally input-only pin into an outbound information channel. Three host conditions enable the attack: a closed-loop amplifier, an exposed amplifier input, and sufficiently high impedance at that pin. Silicon validation on a photoplethysmography analog front-end in 55nm CMOS showed exfiltration at up to 10 kbps with error-free PRBS recovery, under 0.001% area overhead, and only 0.03 dB SNR reduction.

arXiv cs.CR · 10h agoResearch

Crypto customers targeted by scammers after email marketing provider breach

Attackers exploited a Brevo SAML SSO flaw to access 138 accounts and phish crypto customers of Trezor, CoinTracking, and BitBox.

An attacker exploited a flaw in Brevo's SAML SSO handling to access 138 customer accounts on September 10; six accounts were used to send phishing emails and contacts were exported from 43 accounts. Crypto firms Trezor, CoinTracking, and BitBox confirmed customers received phishing emails, with Trezor warning roughly 347,000 newsletter subscribers. The Trezor-themed email cited a fabricated STM32 microcontroller entropy bug and urged recipients to enter wallet backups through a malicious link. Exported contact lists could fuel future targeted phishing attacks.

Malwarebytes Labs · 5d agoData breach in the wild 5 sources

Pre-Whitening and BCJR Posterior Distillation for Bi-LSTM Detection in Faster-than-Nyquist Signaling

Study shows nested-window Bi-LSTM architectures do not improve faster-than-Nyquist detection; pre-whitening plus BCJR distillation cuts bit error rates.

Across roughly 260 controlled trainings, processing nested intersymbol-interference windows in separate recurrent branches never significantly beat a plain Bi-LSTM at matched parameter budgets. The authors attribute the limitation to the observation model rather than architecture, and instead pre-whiten inputs and distill BCJR soft posteriors into the network. With 3.4% more parameters, the method reaches 1.05x the BCJR bit error rate at compression factor 0.8 and 1.89x at 0.7, improving to 1.47x with a wider whitened window.

arXiv cs.AI / cs.LG / cs.CL · 9d agoAI research

Benchmarking Qwen3.8 27B quantizations: 4-bit holds up, 1-bit collapses

Quesma benchmarks Qwen3.8 27B quantizations: 4-bit Q4_K_M matches BF16 on key benchmarks while 1-bit collapses to random chance.

Quesma spent roughly $3,000 on Modal GPUs testing Unsloth GGUF quantizations of Qwen3.8 27B across GPQA Diamond, IFBench, and Terminal-Bench 2.1. The 17 GB Q4_K_M quantization matched the 55 GB BF16 model on Terminal-Bench 2.1 and showed little degradation down to 4-bit, while the 2-bit UD-Q2_K_XL dropped noticeably. At 1-bit, scores on GPQA Diamond fell to random-guess levels, with longer reasoning making results worse, and reasoning effort settings significantly affected outcomes.

Objective vs. Search: Decomposing What Makes a Good Tokenisernew

New tokeniser study shows search procedure, not optimisation objective, drives bits-per-byte performance across model sizes, vocabulary sizes, and multilingual settings.

The paper disentangles BPE and UnigramLM along two axes: optimisation objective (compression vs log-likelihood) and search procedure (bottom-up merging vs top-down pruning). Two new algorithms, BottomUpLL and TopDownComp, complete the 2x2 design space, and trained language models are evaluated on bits-per-byte and BLiMP across model sizes, vocabulary sizes, and English-only vs multilingual domains. Bottom-up tokenisers consistently achieve lower bits-per-byte in most settings, while BLiMP shows no consistent relationship with design choice.

arXiv cs.AI / cs.LG / cs.CL · 10h agoAI research

PuzzleMask: Abusing Plain Prose as a Covert AI Attack Vector

Check Point details PuzzleMask, a plain-prose technique that bypasses LLM gatekeeper policy checks, letting hidden payloads reach target models unreviewed.

Check Point Research describes PuzzleMask, a prompt-crafting technique that hides policy-violating payloads inside plain-English prose wrappers, bypassing quick LLM-based policy checks without emojis, Base64, or invisible formatting. The researchers tested 23 automated prompts against gatekeepers including GPT-4o-mini, GPT-OSS-Safeguard 20b, Claude 3 Haiku, and Llama Guard 3, and all were classified as safe despite policies that flagged the plain versions. When submitted to GPT-5 in thinking-high mode with a Python interpreter, the target model extracted and acted on the payload in over 90% of trials. The technique is not itself a jailbreak but can carry a jailbreak prompt as payload; mitigations include input paraphrasing, hardened gatekeeper policies, and output monitoring.

Check Point Researchupdated · 5d agofirst · 6d agoAI safety & security 2 sources

On APN Functions with Boomerang Uniformity One over $\mathbb F_{3^n}$: Differential and Boomerang Spectra and CCZ-Inequivalence

Cryptographic construction yields infinite APN function families with boomerang uniformity one over odd-characteristic fields, proving CCZ-inequivalence to power functions.

For q=3^n with odd n>1, every sign-switch of a perfect nonlinear Dembowski-Ostrom polynomial is proven APN with boomerang uniformity one or two, attaining uniformity one for (q-3)/2 parameters. This gives the first general construction of infinite APN families achieving boomerang uniformity one over odd-characteristic finite fields. The authors determine common differential and complete boomerang spectra, ruling out CCZ equivalence with power and Ness-Helleseth binomials, and exhibit three pairwise CCZ-inequivalent PN functions for infinitely many n, with the smallest degree n=45.

arXiv cs.CR · 8d agoResearch

Scaling Verification of Cryptographic Software with Aeneas, Rust, and Lean

Microsoft SymCrypt implementations of SHA-3 and ML-KEM verified in Lean via Aeneas-extracted Rust models, with AI agents writing proofs.

The paper develops a methodology for verifying production Rust cryptographic code by using Aeneas to extract pure models into Lean, avoiding low-level pointer and aliasing reasoning. Applied to Microsoft's SymCrypt, it verifies SHA-3 and ML-KEM implementations ported from C to Rust and extends SymCrypt with FrodoKEM, ML-DSA, and HPKE. A 237 KLOC Lean development establishes safety, panic-freedom, and functional correctness of 16.7 KLOC of Rust supporting post-quantum cipher suites on x86-64 and ARM. AI agents autonomously write formal proofs verified by the Lean kernel, and evaluation shows verified Rust meets SymCrypt's performance and portability requirements.

arXiv cs.CR · 2d agoResearch1

Securing quantum error correction against misleading advice from AI agentsnew

Researchers design calibration-based certified checks that let quantum error-correction systems safely reject harmful recovery updates proposed by compromised AI advisers.

The paper shows that opposite coherent X rotations in an odd-distance square toric code yield identical passive syndrome histories, creating ambiguity an AI adviser could exploit to recommend harmful recovery updates. It introduces terminal logical measurements on calibration states plus an independent evaluator that accepts updates only when calibration uncertainty and drift bounds certify improvement. Simulated advice attacks showed calibration-confidence checks reject harmful proposals while retaining most beneficial updates, and the authors derive sufficient limits on calibration age.

arXiv cs.CR · 11h agoAI safety & security

Normal Alignment: Improved Cryptanalytic Sign Recovery on Hard-Label Networksnew

Researchers propose Normal Alignment, improving cryptanalytic sign recovery for hard-label neural networks and enabling polynomial-time full model extraction.

The paper improves on Carlini et al.'s EUROCRYPT 2025 cryptanalytic extraction of hard-label (S1) DNNs, whose Future Toggle sign-recovery method offered only marginal advantage over random guessing and triggered exponential-time enumeration on errors. Normal Alignment infers neuron signs via expected length differences between projected normals of adjacent decision facets at dual points, delivering higher voting accuracy and low-confidence errors. Combined with the SOE extension, it achieves exact polynomial-time full sign recovery: CIFAR-10 (192-64x8-10) and MNIST (64-96x3-32-10) models are fully recovered where the prior method required 2^52 or 2^82 sign guesses.

arXiv cs.CR · 13h agoResearch

Efficient Branch-and-Bound Testing and Verification of zkVMs

ZEBRA verifies zkVM constraint systems via branch-and-bound cardinality counting, finding 11 zero-day bugs across five real-world zkVMs and running 51.5x faster than SMT verification.

ZEBRA reduces zkVM correctness to a solution-set cardinality problem requiring that each constraint system admit exactly one valid execution trace, eliminating redundancies like null-row padding and non-deterministic permutations before counting. It lifts analysis from finite-field witnesses to an integer interval lattice, exploiting that constraints across 5 real-world zkVMs use only 14.0% of theoretical connectivity capacity on average, enabling tight interval propagation. A parallel branch-and-bound search produces concrete counterexamples or certifies absence of violations within a bounded region. ZEBRA discovers 11 zero-day bugs (6 independently confirmed, 3 fixed), is 51.5x faster than SMT-based verification, and verifies 16.5 percentage points more instances.

arXiv cs.CR · 2d agoResearch

Gaming the system: how a Chinese-speaking actor turned Brazilian government sites into an SEO weapon

Check Point identifies Chinese-speaking group Gambling Goblin hijacking Brazilian government domains via malicious Apache modules for SEO-manipulated gambling phishing.

Check Point Research tracks a sustained campaign since mid-2025 against Brazilian government and educational organizations by Gambling Goblin, a Chinese-speaking cybercrime cluster linked to Earth Berberoka. Attackers compile and install malicious Apache modules that silently reverse-proxy visitors to phishing pages impersonating Google Play, Microsoft Store, and Amazon, chaining compromised high-reputation domains to inflate search rankings. The group deploys a heavily obfuscated Linux toolkit including DownPro, AlphaAgent, oRAT, a 3snake-based credential stealer, and SSH brute-forcers, with parallel phishing networks localized for Vietnamese, Spanish, and English victims.

Check Point Research · 14d agoThreat actor

Attackers Exploit Critical Switchvox Flaw to Deploy Reverse Shells Without Credentials

Attackers exploit unauthenticated SQL injection CVE-2026-9586 in Sangoma Switchvox to run PostgreSQL commands and deploy reverse shells.

Threat actors are exploiting CVE-2026-9586 (CVSS 9.3), an unauthenticated SQL injection in Sangoma Switchvox SMB Edition 8.3 (104997), since August 30, 2026, running arbitrary SQL as the PostgreSQL superuser and achieving remote code execution. The /pa endpoint concatenates the user-controlled PhoneIP value into PostgreSQL queries; attackers can extract database contents, escalate to Switchvox web administrator, exfiltrate the cookie signing key to forge authentication, and invoke reverse shells. Sangoma patched the flaw in Switchvox 8.4.0.2 on July 14, 2026, roughly 4,000 instances are internet-exposed (mostly in the US), and honeypot activity from IP 176.65.148.184 deploys reverse shells followed by Base64-encoded process enumeration.

The Hacker News · 14d agoExploit / PoC in the wildCVE-2026-9586

Bias-Induced Crossover in Absolute Capacity of Dense Associative Memory

Analysis shows biased patterns cut dense associative memory capacity from N^(n-1)/ln N to O(N^(n/2)), with a bias-induced crossover.

The paper analyzes dense associative memory capacity for biased centered binary patterns under the Krotov-Hopfield single-site criterion. Unbiased patterns (q=1/2) with order-n polynomial interactions yield capacity of order N^(n-1)/ln N, while fixed bias q<1/2 reduces capacity to O(N^(n/2)) for even n>=4 and O(N^((n+1)/2)) for odd n>=5. A bias-dependent crosstalk mean destabilizes sites carrying the frequent value, and an activity-dependent control potential restores the higher capacity within the conditioned-Gaussian approximation.

arXiv cs.AI / cs.LG / cs.CL · 1d agoAI research

Echo: Learning-based Matching Decompilation using Trusted Back Translationnew

Researchers introduce Echo, a matching decompiler using trusted back-translation that roughly doubles exact-match rates and outperforms GPT-5.6 and Codex on Mirai.

Echo performs matching decompilation by using compilation as trusted feedback for iterative search: a domain-specific model generates candidate code and compilation configurations, which are recompiled, compared at assembly level, and repaired via rule-based rewriting, neural refinement, and reasoning-based refinement. On function-level benchmarks, Echo produces 2.43x more exact matches than the strongest baseline and the highest structural similarity to ground truth. On the Mirai malware binary, it matches 2.75x and 7.4x as many functions as GPT-5.6 and Codex, respectively.

arXiv cs.CR · 14h agoResearch

Closing the Loop: Bidirectional Fully Encrypted Protocols

Researchers show naively composing unidirectional fully encrypted protocols is detectable and construct provably secure bidirectional FEPs, validated in Rust.

The paper introduces formal security definitions for bidirectional fully encrypted protocols (BiFEPs), covering exact shaping, delivery, protocol-state integrity, private half-close, and cross-direction isolation. It shows trivially composing two unidirectional FEPs enables detection attacks via cross-direction dependencies like traffic imbalance and connection tear-down. The authors construct provably secure BiFEPs for datastream and datagram settings, validated with a Rust implementation; no surveyed deployed protocol provides the full set of properties.

arXiv cs.CR · 1d agoResearch

Thin-shell stability of Gaussian cooling: logconcave sampling with sesteric complexity from a cold start

Thin-shell stability proof along the Gaussian cooling path improves cold-start logconcave sampling complexity to near n^2.5 from n^2.75.

The authors prove that logconcave probability measures along the Gaussian cooling path have thin-shell stability, generalizing the thin-shell theorem. This yields improved complexity for sampling an arbitrary logconcave distribution from a cold start. For (near-)isotropic logconcave distributions the complexity is nearly n^2.5, improving the previous n^2.75 bound and matching the abstract Speedy walk.

arXiv cs.AI / cs.LG / cs.CL · 2d agoAI research