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Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026
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Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026
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Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026
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Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026
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Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026
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Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026
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Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026
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Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026
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Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026
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Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026
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Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026
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Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026
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Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026
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Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026
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Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026
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Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026
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Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026
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Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026
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Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026
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Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026
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Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026
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Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026
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Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026
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Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026
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Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026
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Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Quotienting Markov chains by their peripheral invariant subspace separates persistent regime profiles from transient dynamics for stable policy evaluation.
Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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A theory of transitive inference with exceptions shows relational generalization and memorization depend on representational geometry, with pretrained language models exhibiting predicted systematic errors.
Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Language generation in the limit is recast as recall-precision trade-offs, showing that allowing infinitely many vanishing-frequency hallucinations can strictly increase recall when adversaries withhold target portions.
Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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A polynomial-time algorithm robustly estimates elliptical scatter matrices with nearly optimal samples and error beyond Gaussians.
Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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A sequential supersample framework bounds sequential decision-making generalization via roundwise mutual information and faster Bernstein rates, applying to online learning and bandits.
Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Online prediction algorithms achieve calibration error adapting to non-stationarity via $\tilde O(\min\{\sqrt{T}+(TC)^{1/3},\sqrt{KT}\})$ bounds, smoothly interpolating between i.i.d. and adversarial settings.
Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026
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Determinantal sampling builds smaller k-clustering coresets with sub-quadratic ε dependence under mild data assumptions, breaking worst-case bounds.
Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026
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SupSplitLog achieves near-optimal logistic bandit regret without context diversity assumptions via sample splitting and Newton-type corrections.
Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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A profit-maximizing broker achieves tight O√T regret against smooth adversaries in bilateral trade via continuity and hierarchical nets.
Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026
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A selective-classification method estimates label-noise transition matrices with finite-sample guarantees while bypassing fragile class-posterior estimation.
Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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No algorithm achieves O(log η) search on general trees via distance predictions, but O(k log η) queries work for trees of pathwidth k with optimal complexity.
Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026
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Stochastic linear bandits with delayed feedback yield near-optimal, dimension-free additive penalties for loss-independent delays but dimension-dependent penalties for loss-dependent delays, unlike multi-armed bandits.
Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026
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Under truncation hiding an ε-fraction of mass, mean testing faces a bias floor of order ν ε^{1−1/p}; above it a second-order test achieves near-optimal sample complexity, while median regularity restores classical √d testing rates.
Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Intrinsic Riemannian cross-covariance defines manifold-valued covariance via parallel transport to a common tangent space, yielding coordinate-independent second-order descriptors with Euclidean-like properties and verified asymptotic behavior.
Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Transformers approximate α-Hölder functions via softmax partition of unity with two encoder blocks, achieving near minimax-optimal generalization rates.
Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Proposes safe exploration to learn a receiver's unknown belief bias via signaling, achieving optimal O(log log T) regret by exploiting asymmetric probing costs.
Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026
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BROT estimates optimal transport maps via barycentric regression with deep networks, achieving minimax optimal convergence rates under Lipschitz conditions with stable training.
Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Persuasive prediction learns decision-calibrated predictors from data without common priors, matching Bayesian persuasion utility with efficient algorithms.
Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Calibrated human-AI teaming shows combination methods lose human calibration, while delegation preserves predictor calibration but requires an unattainably precise rejector.
Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Byzantine agreement with predictors achieves tight consistency-robustness trade-offs and linear resilience degradation with prediction errors.
Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026
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Consensus ranking distributions approximate ranking distributions via sparse Dirichlet mixtures with optimal Kendall τ distortion expressed through pairwise probabilities, enabling efficient tree-structured statistical learning.
Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026
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This paper develops minimax-optimal estimators for transport-growth pairs in unbalanced optimal transport and proves matching lower bounds via a stability reduction.
Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Multiclass logistic regression learns Gaussian mixtures sequentially by class frequency, producing power-law risk phases and compute-optimal scaling laws.
Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Empirical Bernstein inequalities for bounded self-adjoint operators replace unknown variance with data-driven estimates and scale with intrinsic dimension for dimension-free, infinite-dimensional guarantees.
Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Approximate balanced MDL with additive slack yields finite cumulative squared error for regularization weight lambda at least 1, but multiplicative approximation and lambda under 1 cause failure, establishing additive approximation is essential.
Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Multicalibration gradient boosting converges at O(1/sqrt(T)) with linear rates under smoothness, plus adaptive guarantees backed by experiments.
Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Domination-avoiding learning agents provably avoid collusion in competitive markets and converge to non-dominated strategies.
Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026
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Derives asymptotic anytime-valid confidence sequences for U-statistics via Hoeffding projections and a SAGE boundary, achieving optimal time-uniform rates for both nondegenerate and degenerate cases.
Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026
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Latent prediction learns hierarchical latent trees with samples constant in depth L, exponentially more efficient than token-level self-supervision, making explicit multi-scale stacking largely redundant.
Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 3 on Hugging Face
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Overparameterized pretrained linear models risk transfer learning bias, but combining many with a multiplicative debiasing correction improves target predictions.
Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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A NormalHedge variant achieves second-order ε-quantile regret O(sqrt(V_T log(V_T/ε))) for easy sequences via self-concordance analysis.
Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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An efficient online multicalibration algorithm adaptively refines a dyadic grid to interpolate between worst-case and benign sequences, achieving rates from O(T^{2/3}) down to O(sqrt(T)) and O(sqrt(JT)) with tight threshold-complexity dependence.
Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026
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Multiclass PAC learning with bandit feedback is characterized by the new bandit DS dimension via pseudo-boxes, yielding sharp sample complexity scaling with total neighbors.
Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026
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Online gradient descent achieves optimal O(sqrt(T)) regret for hidden-convex losses via sharper discrete equivalence, with a necessary Hessian compatibility condition and O(T^{3/4}) bandit regret.
Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Pointwise consistency requires a connected co-occurrence graph and PAC learning needs completeness, with optimal sample complexity ranging from nearly linear to quadratic.
Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026
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Capacity-constrained online convex optimization with delayed feedback achieves near-standard regret with logarithmic tracking capacity via randomized scheduling and weighted FTRL.
Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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One-pass SGD analysis of high-dimensional linear regression reveals mixed synthetic training causes model collapse, but two-stage curricula avoid the risk floor via synthetic pretraining.
Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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A projection-free second-order perceptron-style algorithm achieves O(d log T) contextual recommendation regret without Mahalanobis projections, improves efficiency over ONS, and remains robust to suboptimal feedback.
Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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CoCP jointly learns interval centers and radii via alternating quantile regression and soft-coverage optimization, yielding shorter, asymptotically length-optimal conformal intervals with finite-sample validity.
Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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A new lower bound and matching logarithmic-factor upper bound are derived for the sample complexity of 1-identification in multi-armed bandits. The algorithm achieves near-optimal expected pulls uniformly across all instances via a novel optimization formulation.
Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Diagonal regularizers saturate at a prior-driven power law because isotropic truncation noise and eigenvalue counting yield flat loss landscapes, so learned diagonal forms barely beat the closed form and only cross-mode coupling enables real gains.
Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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An online algorithm achieves optimal ε-recalibration with ε² excess error in ε⁻³ rounds via Blackwell approachability, and yields simultaneous calibration and calibeating for smooth losses.
Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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The paper defines truthful multiclass calibration errors for linear label properties, proves they preserve Blackwell informativeness ordering, and show they stabilize model rankings across bin choices.
Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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ToMAToMP extends topological clustering to multiple functions via MMA decomposition, yielding robustness, automatic graph tuning, and outlier resistance with strong empirical gains.
Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026
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Iterative Chow filtering enables efficient PQ learning via L1 sandwiching approximations, yielding quasipolynomial DNF algorithms and exponential improvements for circuits and polynomial thresholds.
Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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A testable learning algorithm learns general Massart halfspaces under Gaussian marginals with quasi-polynomial complexity matching SQ lower bounds.
Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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Multiclass linear classification under Gaussian marginals achieves polynomial-time robust learning via pairwise and localization frameworks, yielding near-optimal error bounds and exposing perceptron limitations.
Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026
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Contrastive identification and generation in the limit studies learning from unlabeled differing pairs, yielding geometric characterizations, a strict generation hierarchy, and robust corruption reversal via common crossing graphs.
Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Certification becomes exponentially hard for slightly overparameterized depth-2+ circuits and constant-overhead transformers, requiring exponentially large example sets and allowing imperfect models to hide errors.
Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Sech perturbation kernels make calibration functions analytic, enabling polynomial regression to estimate second-order calibration error at the minimax optimal rate of tilde O(1/sqrt(n)). This yields the first finite-sample guarantee for second-order Platt scaling and a bucket-free calibration defin
Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Joint KL yields horizon-free approximation and linear estimation bounds, fully characterizing long-sequence autoregressive learning under misspecification.
Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Eventually consistent generators cannot generate high-ranked strings before deadlines, but vanishing hallucination rates enable timely superlinear-deadline coverage, which is impossible under linear deadlines.
Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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STLC improves transductive local complexity bounds via modified log-Sobolev and entropy closure, matching inductive rates without extra logarithmic factors and yielding sharper kernel learning bounds.
Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026
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CQB-η-2 improves contextual queueing bandit queue length regret to O~(T^-1/2) via phased exploration, matching a minimax lower bound.
Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Online set learning with randomized precision or recall feedback is learnable exactly when the hypothesis class has finite VC dimension, though standard empirical risk minimization can fail and algorithms must handle feedback dependencies to achieve regret bounds.
Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026
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A direct Nadaraya-Watson estimator for Schrödinger bridge time-series drifts achieves uniform non-asymptotic bounds, a pointwise CLT, and adaptive minimax optimality by isolating statistical error from optimization errors.
Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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Tree ensemble minimax rates depend on induced kernel eigenvalue decay, and spectral compression yields orders-of-magnitude smaller distilled models with competitive accuracy.
Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Conservative-Markdown Redirect-UCB Pricing achieves optimal Õ(T^{2/3}) regret for contextual dynamic pricing with agnostic non-Lipschitz demand, closing the prior regret gap.
Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026
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