12,194 skills found · Page 281 of 407
brycewang-stanford / aamas-artifact-evaluationUse when packaging AAMAS multiagent code, environments, opponent and population sets, random seeds, game definitions, and logs as anonymous supplementary evidence or a public post-acceptance release, even without a separate artifact badge, so that game-theory and MARL reviewers can inspect and re-ru…
brycewang-stanford / aamas-author-responseUse when drafting an AAMAS rebuttal to preliminary OpenReview reviews, covering the double-blind constraint, the no-new-results and no-revised-paper norms, how to answer game-theory, MARL, and systems reviewers at once, and how to give the area chair a clean acceptance rationale within a short respo…
brycewang-stanford / aamas-experimentsUse when designing or auditing AAMAS experiments - self-play and population-based training, opponent selection, equilibrium and regret metrics, game-theoretic simulations, ablations, seeds, hyperparameters, compute, and claim-to-evidence fit - with emphasis on experiments that probe the interaction…
brycewang-stanford / aamas-related-workUse when positioning an AAMAS submission against multiagent, game-theory, and reinforcement-learning literature spread across AAMAS, AAAI, IJCAI, NeurIPS, ICML, EC, and JAAMAS, including arXiv and workshop versions, concurrent submissions, prior conference versions, and the cross-community citation…
brycewang-stanford / aamas-reproducibilityUse when strengthening AAMAS reproducibility evidence for interaction claims, including proofs and game definitions, opponent and population sets, self-play protocols, random seeds, compute, uncertainty on strategic outcomes, baselines, and consistency between what the paper claims about agents and…
brycewang-stanford / aamas-review-processUse when explaining or planning around AAMAS peer review, covering OpenReview review release, the double-blind rebuttal on preliminary reviews, area-chair discussion, the mixed game-theory, MARL, and systems reviewer pool, the public posting of reviews and decisions, and how acceptance criteria weig…
brycewang-stanford / aamas-supplementaryUse when preparing AAMAS supplementary material - proofs, extended game and mechanism definitions, extra multiagent experiments, opponent-set details, and the anonymized artifact zip - under the size cap, anonymity, and reviewer-discretion limits, including how to split a game-theory-plus-experiment…
brycewang-stanford / aamas-topic-selectionUse when deciding whether a project is a strong AAMAS fit, comparing AAMAS with AAAI, IJCAI, NeurIPS, ICML, EC, and the JAAMAS journal, identifying whether the agents are truly the research object, naming the interaction primitive (solution concept, mechanism, coordination, negotiation), and sharpen…
brycewang-stanford / aamas-workflowUse when planning an AAMAS project timeline from venue fit through abstract, full-paper or extended-abstract upload, supplementary material, the double-blind rebuttal, decision, IFAAMAS camera-ready, registration, and presentation, with track-specific deadlines and backward-planning offsets for a ga…
brycewang-stanford / aamas-writing-styleUse when revising an AAMAS paper so the interaction contribution leads the first page, the solution concept or incentive property is named, the game and agents are legible, claims are paired with proofs or multiagent experiments, the argument fits eight two-column pages plus references, and the word…
brycewang-stanford / ccs-artifact-evaluationUse when packaging ACM CCS artifacts for the artifact-evaluation committee and the ACM badges — Artifacts Available, Artifacts Evaluated Functional, Artifacts Evaluated Reusable, and Results Reproduced — covering what security evaluators inspect, how to make attacks and defenses turnkey, and how to…
brycewang-stanford / ccs-author-responseUse when drafting an ACM CCS rebuttal during the HotCRP author-response window, covering threat-model defenses, adaptive-attack objections, ethics and disclosure questions, anonymity constraints, adversarial reviewer pushback patterns, and decision-focused replies aimed at the meta-reviewer.
brycewang-stanford / ccs-experimentsUse when designing or auditing ACM CCS experiments, attack demonstrations, adaptive-attack defense evaluations, security measurements, baselines, overhead and cost reporting, ablations, and claim-to-evidence fit, with emphasis on evidence that survives an adversarial program committee rather than le…
brycewang-stanford / ccs-related-workUse when positioning an ACM CCS submission against the security big-four and specialist literature, including arXiv preprints, prior CCS/S&P/USENIX/NDSS papers, concurrent disclosures, CVE and advisory records, and the attack-and-defense lineage that a SIGSAC program committee expects to see credite…
brycewang-stanford / ccs-reproducibilityUse when strengthening ACM CCS reproducibility evidence, including the artifact-availability posture, threat-model-to-evidence mapping, attack reproduction steps, defense overhead measurement, measurement-dataset provenance, environment and version pinning, and honest justification when artifacts ca…
brycewang-stanford / ccs-review-processUse when explaining or planning around ACM CCS peer review, the two-cycle HotCRP workflow, decision categories including minor revision, the rebuttal window, the adversarial reviewer pool, ethics and disclosure scrutiny, meta-review dynamics, and ACM proceedings outcomes.
brycewang-stanford / ccs-submissionUse when auditing an ACM CCS submission for HotCRP readiness, dual-cycle abstract registration and full-paper deadlines, the 12-page ACM sigconf body, anonymization, the ethics considerations appendix, artifact-availability posture, dual-submission policy, per-cycle submission caps, desk-reject trig…
brycewang-stanford / ccs-supplementaryUse when preparing ACM CCS appendices and supplementary material, including the ethics considerations appendix, protocol transcripts, formal proofs, measurement tables, and anonymized supporting material under the 12-page body limit, anonymity, and reviewer-discretion constraints for a security pape…
brycewang-stanford / ccs-topic-selectionUse when deciding whether a security project fits ACM CCS versus IEEE S&P, USENIX Security, NDSS, PETS, or a crypto/theory venue, identifying the security contribution type, and sharpening the threat model and attacker capability before writing begins.
brycewang-stanford / ccs-workflowUse when planning an ACM CCS project timeline across the two HotCRP review cycles, from venue fit through abstract registration, full-paper upload, rebuttal, notification, revision, artifact evaluation, ACM camera-ready, and in-person presentation, with backward-planning offsets and the security big…
brycewang-stanford / ccs-writing-styleUse when revising an ACM CCS paper for a precise threat model, calibrated attack/defense claims, 12-page ACM sigconf compression, double-blind wording, adaptive-evaluation honesty, and the security house style that survives an adversarial SIGSAC program committee.
brycewang-stanford / aistats-artifact-evaluationUse when packaging AISTATS code, data, proofs, simulation scripts, notebooks, random seeds, and logs as anonymous supplementary evidence or public post-acceptance artifacts, even when there is no separate artifact badge.
brycewang-stanford / aistats-author-responseUse when drafting AISTATS author responses or author-reviewer discussion replies under OpenReview, covering text-only discussion, no-link guidance, no revised-paper upload, anonymity requirements, statistician-reviewer pushback patterns, and decision-focused clarification strategy for theory-plus-ex…
brycewang-stanford / aistats-camera-readyUse when preparing accepted AISTATS papers for PMLR camera-ready submission, covering the 9-page final body, two-column layout reflow, author de-anonymization, proceedings forms, metadata, final appendix handling, registration, in-person presentation obligations, and public artifact release.
brycewang-stanford / aistats-experimentsUse when designing or auditing AISTATS experiments, simulations, baselines, statistical tests, uncertainty estimates, ablations, random seeds, hyperparameters, compute, dataset handling, and claim-to-evidence fit, with emphasis on experiments that validate theorems rather than chase leaderboards.
brycewang-stanford / aistats-related-workUse when positioning an AISTATS submission against AI, machine-learning, statistics, and uncertainty literature, including arXiv preprints, workshop versions, concurrent submissions, prior conference versions, PMLR archival status, and the two-community citation coverage that AISTATS reviewers expec…
brycewang-stanford / aistats-reproducibilityUse when strengthening AISTATS reproducibility evidence, including the official reproducibility checklist, statistical assumptions, proofs, datasets, hyperparameters, random seeds, compute, uncertainty estimates, baselines, code/data release statements, and checklist-to-claim consistency audits.
brycewang-stanford / aistats-review-processUse when explaining or planning around AISTATS peer review, OpenReview review release, author-reviewer discussion, reviewer volunteer expectations, reviewer confidentiality, decision criteria, meta-review dynamics, the statistician-heavy reviewer pool, and PMLR proceedings outcomes.
brycewang-stanford / aistats-submissionUse when auditing an AISTATS submission for OpenReview readiness, abstract/full-paper deadlines, the 8-page submission body, double-blind anonymity, supplementary material, reproducibility checklist, dual-submission policy, reviewer volunteer requirements, desk-reject triggers, and final-week submis…
brycewang-stanford / aistats-supplementaryUse when preparing AISTATS supplementary material, appendices, proof details, code/data archives, simulation scripts, additional tables, and anonymized artifacts under deadline, size, anonymity, and reviewer-discretion constraints, including how to split a theory-plus-experiments paper between body…
